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regression</title> <meta name="description" content="Search results for: multinomial regression"> <meta name="keywords" content="multinomial regression"> <meta name="viewport" content="width=device-width, initial-scale=1, minimum-scale=1, maximum-scale=1, user-scalable=no"> <meta charset="utf-8"> <link href="https://cdn.waset.org/favicon.ico" type="image/x-icon" rel="shortcut icon"> <link href="https://cdn.waset.org/static/plugins/bootstrap-4.2.1/css/bootstrap.min.css" rel="stylesheet"> <link href="https://cdn.waset.org/static/plugins/fontawesome/css/all.min.css" rel="stylesheet"> <link href="https://cdn.waset.org/static/css/site.css?v=150220211555" rel="stylesheet"> </head> <body> <header> <div class="container"> <nav class="navbar navbar-expand-lg navbar-light"> <a class="navbar-brand" href="https://waset.org"> <img src="https://cdn.waset.org/static/images/wasetc.png" alt="Open Science Research Excellence" title="Open Science Research Excellence" /> </a> <button class="d-block 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action="https://publications.waset.org/abstracts/search"> <div id="custom-search-input"> <div class="input-group"> <i class="fas fa-search"></i> <input type="text" class="search-query" name="q" placeholder="Author, Title, Abstract, Keywords" value="multinomial regression"> <input type="submit" class="btn_search" value="Search"> </div> </div> </form> </div> </div> <div class="row mt-3"> <div class="col-sm-3"> <div class="card"> <div class="card-body"><strong>Commenced</strong> in January 2007</div> </div> </div> <div class="col-sm-3"> <div class="card"> <div class="card-body"><strong>Frequency:</strong> Monthly</div> </div> </div> <div class="col-sm-3"> <div class="card"> <div class="card-body"><strong>Edition:</strong> International</div> </div> </div> <div class="col-sm-3"> <div class="card"> <div class="card-body"><strong>Paper Count:</strong> 3252</div> </div> </div> </div> <h1 class="mt-3 mb-3 text-center" style="font-size:1.6rem;">Search results for: multinomial regression</h1> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">3252</span> A Kolmogorov-Smirnov Type Goodness-Of-Fit Test of Multinomial Logistic Regression Model in Case-Control Studies</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Chen%20Li-Ching">Chen Li-Ching </a> </p> <p class="card-text"><strong>Abstract:</strong></p> The multinomial logistic regression model is used popularly for inferring the relationship of risk factors and disease with multiple categories. This study based on the discrepancy between the nonparametric maximum likelihood estimator and semiparametric maximum likelihood estimator of the cumulative distribution function to propose a Kolmogorov-Smirnov type test statistic to assess adequacy of the multinomial logistic regression model for case-control data. A bootstrap procedure is presented to calculate the critical value of the proposed test statistic. Empirical type I error rates and powers of the test are performed by simulation studies. Some examples will be illustrated the implementation of the test. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=case-control%20studies" title="case-control studies">case-control studies</a>, <a href="https://publications.waset.org/abstracts/search?q=goodness-of-fit%20test" title=" goodness-of-fit test"> goodness-of-fit test</a>, <a href="https://publications.waset.org/abstracts/search?q=Kolmogorov-Smirnov%20test" title=" Kolmogorov-Smirnov test"> Kolmogorov-Smirnov test</a>, <a href="https://publications.waset.org/abstracts/search?q=multinomial%20logistic%20regression" title=" multinomial logistic regression"> multinomial logistic regression</a> </p> <a href="https://publications.waset.org/abstracts/44967/a-kolmogorov-smirnov-type-goodness-of-fit-test-of-multinomial-logistic-regression-model-in-case-control-studies" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/44967.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">456</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">3251</span> Use of Multistage Transition Regression Models for Credit Card Income Prediction</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Denys%20Osipenko">Denys Osipenko</a>, <a href="https://publications.waset.org/abstracts/search?q=Jonathan%20Crook"> Jonathan Crook</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Because of the variety of the card holders’ behaviour types and income sources each consumer account can be transferred to a variety of states. Each consumer account can be inactive, transactor, revolver, delinquent, defaulted and requires an individual model for the income prediction. The estimation of transition probabilities between statuses at the account level helps to avoid the memorylessness of the Markov Chains approach. This paper investigates the transition probabilities estimation approaches to credit cards income prediction at the account level. The key question of empirical research is which approach gives more accurate results: multinomial logistic regression or multistage conditional logistic regression with binary target. Both models have shown moderate predictive power. Prediction accuracy for conditional logistic regression depends on the order of stages for the conditional binary logistic regression. On the other hand, multinomial logistic regression is easier for usage and gives integrate estimations for all states without priorities. Thus further investigations can be concentrated on alternative modeling approaches such as discrete choice models. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=multinomial%20regression" title="multinomial regression">multinomial regression</a>, <a href="https://publications.waset.org/abstracts/search?q=conditional%20logistic%20regression" title=" conditional logistic regression"> conditional logistic regression</a>, <a href="https://publications.waset.org/abstracts/search?q=credit%20account%20state" title=" credit account state"> credit account state</a>, <a href="https://publications.waset.org/abstracts/search?q=transition%20probability" title=" transition probability"> transition probability</a> </p> <a href="https://publications.waset.org/abstracts/19488/use-of-multistage-transition-regression-models-for-credit-card-income-prediction" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/19488.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">486</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">3250</span> A Study of Classification Models to Predict Drill-Bit Breakage Using Degradation Signals</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Bharatendra%20Rai">Bharatendra Rai</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Cutting tools are widely used in manufacturing processes and drilling is the most commonly used machining process. Although drill-bits used in drilling may not be expensive, their breakage can cause damage to expensive work piece being drilled and at the same time has major impact on productivity. Predicting drill-bit breakage, therefore, is important in reducing cost and improving productivity. This study uses twenty features extracted from two degradation signals viz., thrust force and torque. The methodology used involves developing and comparing decision tree, random forest, and multinomial logistic regression models for classifying and predicting drill-bit breakage using degradation signals. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=degradation%20signal" title="degradation signal">degradation signal</a>, <a href="https://publications.waset.org/abstracts/search?q=drill-bit%20breakage" title=" drill-bit breakage"> drill-bit breakage</a>, <a href="https://publications.waset.org/abstracts/search?q=random%20forest" title=" random forest"> random forest</a>, <a href="https://publications.waset.org/abstracts/search?q=multinomial%20logistic%20regression" title=" multinomial logistic regression"> multinomial logistic regression</a> </p> <a href="https://publications.waset.org/abstracts/13494/a-study-of-classification-models-to-predict-drill-bit-breakage-using-degradation-signals" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/13494.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">352</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">3249</span> A Multinomial Logistic Regression Analysis of Factors Influencing Couples' Fertility Preferences in Kenya</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Naomi%20W.%20Maina">Naomi W. Maina</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Fertility preference is a subject of great significance in developing countries. Studies reveal that the preferences of fertility are actually significant in determining the society’s fertility levels because the fertility behavior of the future has a high likelihood of falling under the effect of currently observed fertility inclinations. The objective of this study was to establish the factors associated with fertility preference amongst couples in Kenya by fitting a multinomial logistic regression model against 5,265 couple data obtained from Kenya demographic health survey 2014. Results revealed that the type of place of residence, the region of residence, age and spousal age gap significantly influence desire for additional children among couples in Kenya. There was the notable high likelihood of couples living in rural settlements having similar fertility preference compared to those living in urban settlements. Moreover, geographical disparities such as in northern Kenya revealed significant differences in a couples desire to have additional children compared to Nairobi. The odds of a couple’s desire for additional children were further observed to vary dependent on either the wife or husbands age and to a large extent the spousal age gap. Evidenced from the study, was the fact that as spousal age gap increases, the desire for more children amongst couples decreases. Insights derived from this study would be attractive to demographers, health practitioners, policymakers, and non-governmental organizations implementing fertility related interventions in Kenya among other stakeholders. Moreover, with the adoption of devolution, there is a clear need for adoption of population policies that are County specific as opposed to a national population policy as is the current practice in Kenya. Additionally, researchers or students who have little understanding in the application of multinomial logistic regression, both theoretical understanding and practical analysis in SPSS as well as application on real datasets, will find this article useful. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=couples%27%20desire" title="couples' desire">couples' desire</a>, <a href="https://publications.waset.org/abstracts/search?q=fertility" title=" fertility"> fertility</a>, <a href="https://publications.waset.org/abstracts/search?q=fertility%20preference" title=" fertility preference"> fertility preference</a>, <a href="https://publications.waset.org/abstracts/search?q=multinomial%20regression%20analysis" title=" multinomial regression analysis"> multinomial regression analysis</a> </p> <a href="https://publications.waset.org/abstracts/88937/a-multinomial-logistic-regression-analysis-of-factors-influencing-couples-fertility-preferences-in-kenya" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/88937.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">181</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">3248</span> Hybrid Model for Measuring the Hedge Strategy in Exchange Risk in Information Technology Industry</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Yi-Hsien%20Wang">Yi-Hsien Wang</a>, <a href="https://publications.waset.org/abstracts/search?q=Fu-Ju%20Yang"> Fu-Ju Yang</a>, <a href="https://publications.waset.org/abstracts/search?q=Hwa-Rong%20Shen"> Hwa-Rong Shen</a>, <a href="https://publications.waset.org/abstracts/search?q=Rui-Lin%20Tseng"> Rui-Lin Tseng</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The business is notably related to the market risk according to the increase of liberalization of financial markets. Hence, the company usually utilized high financial leverage of derivatives to hedge the risk. When the company choose different hedging instruments to face a variety of exchange rate risk, we employ the Multinomial Logistic-AHP to analyze the impact of various derivatives. Hence, the research summarized the literature on relevant factors affecting managers selected exchange rate hedging instruments, using Multinomial Logistic Model and and further integrate AHP. Using Experts’ Questionnaires can test multi-level selection and hedging effect of different hedging instruments in order to calculate the hedging instruments and the multi-level factors of weights to understand the gap between the empirical results and practical operation. Finally, the Multinomial Logistic-AHP Model will sort the weights to analyze. The research findings can be a basis reference for investors in decision-making. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=exchange%20rate%20risk" title="exchange rate risk">exchange rate risk</a>, <a href="https://publications.waset.org/abstracts/search?q=derivatives" title=" derivatives"> derivatives</a>, <a href="https://publications.waset.org/abstracts/search?q=hedge" title=" hedge"> hedge</a>, <a href="https://publications.waset.org/abstracts/search?q=multinomial%20logistic-AHP" title=" multinomial logistic-AHP"> multinomial logistic-AHP</a> </p> <a href="https://publications.waset.org/abstracts/7564/hybrid-model-for-measuring-the-hedge-strategy-in-exchange-risk-in-information-technology-industry" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/7564.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">442</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">3247</span> Mainstreaming Willingness among Black Owned Informal Small Micro Micro Enterprises in South Africa</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Harris%20Maduku">Harris Maduku</a>, <a href="https://publications.waset.org/abstracts/search?q=Irrshad%20Kaseeram"> Irrshad Kaseeram</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The objective of this paper is to understand the factors behind the formalisation willingness of South African black owned SMMEs. Cross-sectional data were collected using a questionnaire from 390 informal businesses in Johannesburg and Pretoria using stratified random sampling and clustered sampling. This study employed a multinomial logistic regression to quantitatively understand what encourages informal SMMEs to be willing to mainstreaming their operations. We find government support, corruption, employment compensation, family labour, success perception, education status, age and financing as key drivers on willingness of SMMEs to formalize their operations. The findings of our study points to government departments to invest more on both financial and non-financial strategies like capacity building and business education on informal SMMEs to cultivate their willingness to mainstream. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=mainstreaming" title="mainstreaming">mainstreaming</a>, <a href="https://publications.waset.org/abstracts/search?q=transition" title=" transition"> transition</a>, <a href="https://publications.waset.org/abstracts/search?q=informal" title=" informal"> informal</a>, <a href="https://publications.waset.org/abstracts/search?q=willingness" title=" willingness"> willingness</a>, <a href="https://publications.waset.org/abstracts/search?q=multinomial%20logit" title=" multinomial logit"> multinomial logit</a> </p> <a href="https://publications.waset.org/abstracts/105837/mainstreaming-willingness-among-black-owned-informal-small-micro-micro-enterprises-in-south-africa" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/105837.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">154</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">3246</span> Urban Household Waste Disposal Modes and Their Determinants: Evidence from Bure Town, North-Western Ethiopia</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Mastawal%20Melese">Mastawal Melese</a>, <a href="https://publications.waset.org/abstracts/search?q=Yismaw%20Assefa"> Yismaw Assefa</a> </p> <p class="card-text"><strong>Abstract:</strong></p> This study aims to identify household-level determinants of solid waste disposal (SWD) practices in Bure Town, north-western Ethiopia. Using a cross-sectional design and a mixed-methods approach, data were collected from 238 randomly selected households through structured interviews, focus group discussions, and field observations. Descriptive analysis revealed that 14.7% of households used composting as a primary SWD method, 37.4% practiced open dumping, 25.6% used burning, and 22.3% resorted to burial. Multinomial logistic regression showed that factors such as monthly income, age, family size, length of residence, sex, home ownership, solid waste sorting procedures, and education significantly influenced the choice of disposal method. Households with lower education, income, home ownership, and shorter residence times were more likely to use improper disposal methods. Females were found to be more likely to engage in better waste disposal practices than males. These findings underscore the need for context-specific interventions in newly developing towns to enhance household-level SWM systems by addressing key socio-economic factors. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=multinomial%20logistic%20regression" title="multinomial logistic regression">multinomial logistic regression</a>, <a href="https://publications.waset.org/abstracts/search?q=solid%20waste%20management" title=" solid waste management"> solid waste management</a>, <a href="https://publications.waset.org/abstracts/search?q=solid%20waste%20disposal" title=" solid waste disposal"> solid waste disposal</a>, <a href="https://publications.waset.org/abstracts/search?q=urban%20household" title=" urban household"> urban household</a> </p> <a href="https://publications.waset.org/abstracts/191910/urban-household-waste-disposal-modes-and-their-determinants-evidence-from-bure-town-north-western-ethiopia" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/191910.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">20</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">3245</span> Study on the Factors Influencing the Built Environment of Residential Areas on the Lifestyle Walking Trips of the Elderly</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Daming%20Xu">Daming Xu</a>, <a href="https://publications.waset.org/abstracts/search?q=Yuanyuan%20Wang"> Yuanyuan Wang</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Abstract: Under the trend of rapid expansion of urbanization, the motorized urban characteristics become more and more obvious, and the walkability of urban space is seriously affected. The construction of walkability of space, as the main mode of travel for the elderly in their daily lives, has become more and more important in the current social context of serious aging. Settlement is the most basic living unit of residents, and daily shopping, medical care, and other daily trips are closely related to the daily life of the elderly. Therefore, it is of great practical significance to explore the impact of built environment on elderly people's daily walking trips at the settlement level for the construction of pedestrian-friendly settlements for the elderly. The study takes three typical settlements in Harbin Daoli District in three different periods as examples and obtains data on elderly people's walking trips and built environment characteristics through field research, questionnaire distribution, and internet data acquisition. Finally, correlation analysis and multinomial logistic regression model were applied to analyze the influence mechanism of built environment on elderly people's walkability based on the control of personal attribute variables in order to provide reference and guidance for the construction of walkability for elderly people in built environment in the future. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=built%20environment" title="built environment">built environment</a>, <a href="https://publications.waset.org/abstracts/search?q=elderly" title=" elderly"> elderly</a>, <a href="https://publications.waset.org/abstracts/search?q=walkability" title=" walkability"> walkability</a>, <a href="https://publications.waset.org/abstracts/search?q=multinomial%20logistic%20regression%20model" title=" multinomial logistic regression model"> multinomial logistic regression model</a> </p> <a href="https://publications.waset.org/abstracts/164764/study-on-the-factors-influencing-the-built-environment-of-residential-areas-on-the-lifestyle-walking-trips-of-the-elderly" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/164764.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">76</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">3244</span> Modelling the Effect of Physical Environment Factors on Child Pedestrian Severity Collisions in Malaysia: A Multinomial Logistic Regression Analysis</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Muhamad%20N.%20Borhan">Muhamad N. Borhan</a>, <a href="https://publications.waset.org/abstracts/search?q=Nur%20S.%20Darus"> Nur S. Darus</a>, <a href="https://publications.waset.org/abstracts/search?q=Siti%20Z.%20Ishak"> Siti Z. Ishak</a>, <a href="https://publications.waset.org/abstracts/search?q=Rozmi%20Ismail"> Rozmi Ismail</a>, <a href="https://publications.waset.org/abstracts/search?q=Siti%20F.%20M.%20Razali"> Siti F. M. Razali</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Children are at the greater risk to be involved in road traffic collisions due to the complex interaction of various elements in our transportation system. It encompasses interactions between the elements of children and driver behavior along with physical and social environment factors. The present study examined the effect between the collisions severity and physical environment factors on child pedestrian collisions. The severity of collisions is categorized into four injury outcomes: fatal, serious injury, slight injury, and damage. The sample size comprised of 2487 cases of child pedestrian-vehicle collisions in which children aged 7 to 12 years old was involved in Malaysia for the years 2006-2015. A multinomial logistic regression was applied to establish the effect between severity levels and physical environment factors. The results showed that eight contributing factors influence the probability of an injury road surface material, traffic system, road marking, control type, lighting condition, type of location, land use and road surface condition. Understanding the effect of physical environment factors may contribute to the improvement of physical environment design and decrease the collision involvement. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=child%20pedestrian" title="child pedestrian">child pedestrian</a>, <a href="https://publications.waset.org/abstracts/search?q=collisions" title=" collisions"> collisions</a>, <a href="https://publications.waset.org/abstracts/search?q=primary%20school" title=" primary school"> primary school</a>, <a href="https://publications.waset.org/abstracts/search?q=road%20injuries" title=" road injuries"> road injuries</a> </p> <a href="https://publications.waset.org/abstracts/98329/modelling-the-effect-of-physical-environment-factors-on-child-pedestrian-severity-collisions-in-malaysia-a-multinomial-logistic-regression-analysis" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/98329.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">164</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">3243</span> Poverty Dynamics in Thailand: Evidence from Household Panel Data</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Nattabhorn%20Leamcharaskul">Nattabhorn Leamcharaskul</a> </p> <p class="card-text"><strong>Abstract:</strong></p> This study aims to examine determining factors of the dynamics of poverty in Thailand by using panel data of 3,567 households in 2007-2017. Four techniques of estimation are employed to analyze the situation of poverty across households and time periods: the multinomial logit model, the sequential logit model, the quantile regression model, and the difference in difference model. Households are categorized based on their experiences into 5 groups, namely chronically poor, falling into poverty, re-entering into poverty, exiting from poverty and never poor households. Estimation results emphasize the effects of demographic and socioeconomic factors as well as unexpected events on the economic status of a household. It is found that remittances have positive impact on household’s economic status in that they are likely to lower the probability of falling into poverty or trapping in poverty while they tend to increase the probability of exiting from poverty. In addition, not only receiving a secondary source of household income can raise the probability of being a never poor household, but it also significantly increases household income per capita of the chronically poor and falling into poverty households. Public work programs are recommended as an important tool to relieve household financial burden and uncertainty and thus consequently increase a chance for households to escape from poverty. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=difference%20in%20difference" title="difference in difference">difference in difference</a>, <a href="https://publications.waset.org/abstracts/search?q=dynamic" title=" dynamic"> dynamic</a>, <a href="https://publications.waset.org/abstracts/search?q=multinomial%20logit%20model" title=" multinomial logit model"> multinomial logit model</a>, <a href="https://publications.waset.org/abstracts/search?q=panel%20data" title=" panel data"> panel data</a>, <a href="https://publications.waset.org/abstracts/search?q=poverty" title=" poverty"> poverty</a>, <a href="https://publications.waset.org/abstracts/search?q=quantile%20regression" title=" quantile regression"> quantile regression</a>, <a href="https://publications.waset.org/abstracts/search?q=remittance" title=" remittance"> remittance</a>, <a href="https://publications.waset.org/abstracts/search?q=sequential%20logit%20model" title=" sequential logit model"> sequential logit model</a>, <a href="https://publications.waset.org/abstracts/search?q=Thailand" title=" Thailand"> Thailand</a>, <a href="https://publications.waset.org/abstracts/search?q=transfer" title=" transfer"> transfer</a> </p> <a href="https://publications.waset.org/abstracts/165351/poverty-dynamics-in-thailand-evidence-from-household-panel-data" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/165351.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">112</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">3242</span> Agroforestry Systems and Practices and Its Adoption in Kilombero Cluster of Sagcot, Tanzania</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Lazaro%20E.%20Nnko">Lazaro E. Nnko</a>, <a href="https://publications.waset.org/abstracts/search?q=Japhet%20J.%20Kashaigili"> Japhet J. Kashaigili</a>, <a href="https://publications.waset.org/abstracts/search?q=Gerald%20C.%20Monela"> Gerald C. Monela</a>, <a href="https://publications.waset.org/abstracts/search?q=Pantaleo%20K.%20T.%20Munishi"> Pantaleo K. T. Munishi</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Agroforestry systems and practices are perceived to improve livelihood and sustainable management of natural resources. However, their adoption in various regions differs with the biophysical conditions and societal characteristics. This study was conducted in Kilombero District to investigate the factors influencing the adoption of different agroforestry systems and practices in agro-ecosystems and farming systems. A household survey, key informant interviews, and focus group discussion was used for data collection in three villages. Descriptive statistics and multinomial logistic regression in SPSS were applied for analysis. Results show that Igima and Ngajengwa villages had home garden practices dominated, as revealed by 63.3% and 66.7%, respectively, while Mbingu village had mixed intercropping practice with 56.67%. Agrosilvopasture systems were dominant in Igima and Ngajengwa villages with 56.7% and 66.7%, respectively, while in Mbingu village, the dominant system was agrosilviculture with 66.7%. The results from multinomial logistic regression show that different explanatory variable was statistical significance as predictors of the adoption of agroforestry systems and practices. Residence type and sex were the most dominant factor influencing the adoption of agroforestry systems. Duration of stay in the village, availability of extension education, residence, and sex were the dominant factor influencing the adoption of agroforestry practices. The most important and statistically significant factors among these were residence type and sex. The study concludes that agroforestry will be more successful if the local priorities, which include social-economic need characteristics of the society, will be considered in designing systems and practices. The socio-economic need of the community should be addressed in the process of expanding the adoption of agroforestry systems and practices. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=agroforestry%20adoption" title="agroforestry adoption">agroforestry adoption</a>, <a href="https://publications.waset.org/abstracts/search?q=agroforestry%20systems" title=" agroforestry systems"> agroforestry systems</a>, <a href="https://publications.waset.org/abstracts/search?q=agroforestry%20practices" title=" agroforestry practices"> agroforestry practices</a>, <a href="https://publications.waset.org/abstracts/search?q=agroforestry" title=" agroforestry"> agroforestry</a>, <a href="https://publications.waset.org/abstracts/search?q=Kilombero" title=" Kilombero"> Kilombero</a> </p> <a href="https://publications.waset.org/abstracts/150353/agroforestry-systems-and-practices-and-its-adoption-in-kilombero-cluster-of-sagcot-tanzania" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/150353.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">118</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">3241</span> Multinomial Dirichlet Gaussian Process Model for Classification of Multidimensional Data</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Wanhyun%20Cho">Wanhyun Cho</a>, <a href="https://publications.waset.org/abstracts/search?q=Soonja%20Kang"> Soonja Kang</a>, <a href="https://publications.waset.org/abstracts/search?q=Sanggoon%20Kim"> Sanggoon Kim</a>, <a href="https://publications.waset.org/abstracts/search?q=Soonyoung%20Park"> Soonyoung Park</a> </p> <p class="card-text"><strong>Abstract:</strong></p> We present probabilistic multinomial Dirichlet classification model for multidimensional data and Gaussian process priors. Here, we have considered an efficient computational method that can be used to obtain the approximate posteriors for latent variables and parameters needed to define the multiclass Gaussian process classification model. We first investigated the process of inducing a posterior distribution for various parameters and latent function by using the variational Bayesian approximations and important sampling method, and next we derived a predictive distribution of latent function needed to classify new samples. The proposed model is applied to classify the synthetic multivariate dataset in order to verify the performance of our model. Experiment result shows that our model is more accurate than the other approximation methods. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=multinomial%20dirichlet%20classification%20model" title="multinomial dirichlet classification model">multinomial dirichlet classification model</a>, <a href="https://publications.waset.org/abstracts/search?q=Gaussian%20process%20priors" title=" Gaussian process priors"> Gaussian process priors</a>, <a href="https://publications.waset.org/abstracts/search?q=variational%20Bayesian%20approximation" title=" variational Bayesian approximation"> variational Bayesian approximation</a>, <a href="https://publications.waset.org/abstracts/search?q=importance%20sampling" title=" importance sampling"> importance sampling</a>, <a href="https://publications.waset.org/abstracts/search?q=approximate%20posterior%20distribution" title=" approximate posterior distribution"> approximate posterior distribution</a>, <a href="https://publications.waset.org/abstracts/search?q=marginal%20likelihood%20evidence" title=" marginal likelihood evidence"> marginal likelihood evidence</a> </p> <a href="https://publications.waset.org/abstracts/33816/multinomial-dirichlet-gaussian-process-model-for-classification-of-multidimensional-data" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/33816.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">444</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">3240</span> Beyond Adoption: Econometric Analysis of Impacts of Farmer Innovation Systems and Improved Agricultural Technologies on Rice Yield in Ghana</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Franklin%20N.%20Mabe">Franklin N. Mabe</a>, <a href="https://publications.waset.org/abstracts/search?q=Samuel%20A.%20Donkoh"> Samuel A. Donkoh</a>, <a href="https://publications.waset.org/abstracts/search?q=Seidu%20Al-Hassan"> Seidu Al-Hassan</a> </p> <p class="card-text"><strong>Abstract:</strong></p> In order to increase and bridge the differences in rice yield, many farmers have resorted to adopting Farmer Innovation Systems (FISs) and Improved Agricultural Technologies (IATs). This study econometrically analysed the impacts of adoption of FISs and IATs on rice yield using multinomial endogenous switching regression (MESR). Nine-hundred and seven (907) rice farmers from Guinea Savannah Zone (GSZ), Forest Savannah Transition Zone (FSTZ) and Coastal Savannah Zone (CSZ) were used for the study. The study used both primary and secondary data. FBO advice, rice farming experience and distance from farming communities to input markets increase farmers’ adoption of only FISs. Factors that increase farmers’ probability of adopting only IATs are access to extension advice, credit, improved seeds and contract farming. Farmers located in CSZ have higher probability of adopting only IATs than their counterparts living in other agro-ecological zones. Age and access to input subsidy increase the probability of jointly adopting FISs and IATs. FISs and IATs have heterogeneous impact on rice yield with adoption of only IATs having the highest impact followed by joint adoption of FISs and IATs. It is important for stakeholders in rice subsector to champion the provision of improved rice seeds, the intensification of agricultural extension services and contract farming concept. Researchers should endeavour to researched into FISs. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=farmer%20innovation%20systems" title="farmer innovation systems">farmer innovation systems</a>, <a href="https://publications.waset.org/abstracts/search?q=improved%20agricultural%20technologies" title=" improved agricultural technologies"> improved agricultural technologies</a>, <a href="https://publications.waset.org/abstracts/search?q=multinomial%20endogenous%20switching%20regression" title=" multinomial endogenous switching regression"> multinomial endogenous switching regression</a>, <a href="https://publications.waset.org/abstracts/search?q=treatment%20effect" title=" treatment effect"> treatment effect</a> </p> <a href="https://publications.waset.org/abstracts/91512/beyond-adoption-econometric-analysis-of-impacts-of-farmer-innovation-systems-and-improved-agricultural-technologies-on-rice-yield-in-ghana" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/91512.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">425</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">3239</span> Adoption of Climate-Smart Agriculture Practices Among Farmers and Its Effect on Crop Revenue in Ethiopia</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Fikiru%20Temesgen%20Gelata">Fikiru Temesgen Gelata</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Food security, adaptation, and climate change mitigation are all problems that can be resolved simultaneously with Climate-Smart Agriculture (CSA). This study examines determinants of climate-smart agriculture (CSA) practices among smallholder farmers, aiming to understand the factors guiding adoption decisions and evaluate the impact of CSA on smallholder farmer income in the study areas. For this study, three-stage sampling techniques were applied to select 230 smallholders randomly. Mann-Kendal test and multinomial endogenous switching regression model were used to analyze trends of decrease or increase within long-term temporal data and the impact of CSA on the smallholder farmer income, respectively. Findings revealed education level, household size, land ownership, off-farm income, climate information, and contact with extension agents found to be highly adopted CSA practices. On the contrary, erosion exerted a detrimental impact on all the agricultural practices examined within the study region. Various factors such as farming methods, the size of farms, proximity to irrigated farmlands, availability of extension services, distance to market hubs, and access to weather forecasts were recognized as key determinants influencing the adoption of CSA practices. The multinomial endogenous switching regression model (MESR) revealed that joint adoption of crop rotation and soil and water conservation practices significantly increased farm income by 1,107,245 ETB. The study recommends that counties and governments should prioritize addressing climate change in their development agendas to increase the adoption of climate-smart farming techniques. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=climate-smart%20practices" title="climate-smart practices">climate-smart practices</a>, <a href="https://publications.waset.org/abstracts/search?q=food%20security" title=" food security"> food security</a>, <a href="https://publications.waset.org/abstracts/search?q=Oincome" title=" Oincome"> Oincome</a>, <a href="https://publications.waset.org/abstracts/search?q=MERM" title=" MERM"> MERM</a>, <a href="https://publications.waset.org/abstracts/search?q=Ethiopia" title=" Ethiopia"> Ethiopia</a> </p> <a href="https://publications.waset.org/abstracts/190107/adoption-of-climate-smart-agriculture-practices-among-farmers-and-its-effect-on-crop-revenue-in-ethiopia" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/190107.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">34</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">3238</span> Behind Fuzzy Regression Approach: An Exploration Study</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Lavinia%20B.%20Dulla">Lavinia B. Dulla</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The exploration study of the fuzzy regression approach attempts to present that fuzzy regression can be used as a possible alternative to classical regression. It likewise seeks to assess the differences and characteristics of simple linear regression and fuzzy regression using the width of prediction interval, mean absolute deviation, and variance of residuals. Based on the simple linear regression model, the fuzzy regression approach is worth considering as an alternative to simple linear regression when the sample size is between 10 and 20. As the sample size increases, the fuzzy regression approach is not applicable to use since the assumption regarding large sample size is already operating within the framework of simple linear regression. Nonetheless, it can be suggested for a practical alternative when decisions often have to be made on the basis of small data. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=fuzzy%20regression%20approach" title="fuzzy regression approach">fuzzy regression approach</a>, <a href="https://publications.waset.org/abstracts/search?q=minimum%20fuzziness%20criterion" title=" minimum fuzziness criterion"> minimum fuzziness criterion</a>, <a href="https://publications.waset.org/abstracts/search?q=interval%20regression" title=" interval regression"> interval regression</a>, <a href="https://publications.waset.org/abstracts/search?q=prediction%20interval" title=" prediction interval"> prediction interval</a> </p> <a href="https://publications.waset.org/abstracts/139364/behind-fuzzy-regression-approach-an-exploration-study" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/139364.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">298</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">3237</span> Analyzing Impacts of Road Network on Vegetation Using Geographic Information System and Remote Sensing Techniques</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Elizabeth%20Malebogo%20Mosepele"> Elizabeth Malebogo Mosepele</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Road transport has become increasingly common in the world; people rely on road networks for transportation purpose on a daily basis. However, environmental impact of roads on surrounding landscapes extends their potential effects even further. This study investigates the impact of road network on natural vegetation. The study will provide baseline knowledge regarding roadside vegetation and would be helpful in future for conservation of biodiversity along the road verges and improvements of road verges. The general hypothesis of this study is that the amount and condition of road side vegetation could be explained by road network conditions. Remote sensing techniques were used to analyze vegetation conditions. Landsat 8 OLI image was used to assess vegetation cover condition. NDVI image was generated and used as a base from which land cover classes were extracted, comprising four categories viz. healthy vegetation, degraded vegetation, bare surface, and water. The classification of the image was achieved using the supervised classification technique. Road networks were digitized from Google Earth. For observed data, transect based quadrats of 50*50 m were conducted next to road segments for vegetation assessment. Vegetation condition was related to road network, with the multinomial logistic regression confirming a significant relationship between vegetation condition and road network. The null hypothesis formulated was that 'there is no variation in vegetation condition as we move away from the road.' Analysis of vegetation condition revealed degraded vegetation within close proximity of a road segment and healthy vegetation as the distance increase away from the road. The Chi Squared value was compared with critical value of 3.84, at the significance level of 0.05 to determine the significance of relationship. Given that the Chi squared value was 395, 5004, the null hypothesis was therefore rejected; there is significant variation in vegetation the distance increases away from the road. The conclusion is that the road network plays an important role in the condition of vegetation. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=Chi%20squared" title="Chi squared">Chi squared</a>, <a href="https://publications.waset.org/abstracts/search?q=geographic%20information%20system" title=" geographic information system"> geographic information system</a>, <a href="https://publications.waset.org/abstracts/search?q=multinomial%20logistic%20regression" title=" multinomial logistic regression"> multinomial logistic regression</a>, <a href="https://publications.waset.org/abstracts/search?q=remote%20sensing" title=" remote sensing"> remote sensing</a>, <a href="https://publications.waset.org/abstracts/search?q=road%20side%20vegetation" title=" road side vegetation"> road side vegetation</a> </p> <a href="https://publications.waset.org/abstracts/79182/analyzing-impacts-of-road-network-on-vegetation-using-geographic-information-system-and-remote-sensing-techniques" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/79182.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">432</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">3236</span> Smallholder Participation in Organized Retail Markets: Evidence from India</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Kedar%20Vishnu">Kedar Vishnu</a>, <a href="https://publications.waset.org/abstracts/search?q=Parmod%20Kumar"> Parmod Kumar </a> </p> <p class="card-text"><strong>Abstract:</strong></p> India is becoming most favored retail destination in the world. The organized retail has presented many opportunities to farmers to increase income by shifting cropping pattern from food grains to commercial crops. Previous research revealed potential benefits for farmers by supplying fruits and vegetables to organized retail channels. However the supply of fruits and vegetables from small and marginal farmers remain low than expected. The main objective of this paper is to identify the factors determining market participation of smallholder farmers in modern organized retail chains. Attempt is also made to find out factors influencing the choice of participation in particular organized retail collection centers as compared to other organized retail. The paper was based on primary survey of 40 Beans and Tomato farmers who supply to organized retail collection centers from Karnataka, India. Multiple regression technique is used to identify the factors determining quantity sold at collection centers. The regression result, show that area under vegetables, yield, and price from modern collection center and having access to technical help were found significantly affecting quantity sold into modern organized retail channels. On the opposite, increased rejection rates and vegetable prices at APMC were found influencing farmers decision into the reverse side. Empirical result of the multinomial logit model show that Reliance fresh has tendency to prefer large farmers who can supply more quality and better quantity compared with TESCO and More collection centers. The negative sign of area, having access to technical help, transportation cost, and number of bore wells led to higher probability of farmers to participate in Reliance Fresh collection centers as compared with More and TESCO. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=fruits" title="fruits">fruits</a>, <a href="https://publications.waset.org/abstracts/search?q=vegetables" title=" vegetables"> vegetables</a>, <a href="https://publications.waset.org/abstracts/search?q=organized%20retail%20markets" title=" organized retail markets"> organized retail markets</a>, <a href="https://publications.waset.org/abstracts/search?q=multinomial%20logit%20model" title=" multinomial logit model"> multinomial logit model</a> </p> <a href="https://publications.waset.org/abstracts/23812/smallholder-participation-in-organized-retail-markets-evidence-from-india" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/23812.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">345</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">3235</span> Optimization of Machine Learning Regression Results: An Application on Health Expenditures</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Songul%20Cinaroglu">Songul Cinaroglu</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Machine learning regression methods are recommended as an alternative to classical regression methods in the existence of variables which are difficult to model. Data for health expenditure is typically non-normal and have a heavily skewed distribution. This study aims to compare machine learning regression methods by hyperparameter tuning to predict health expenditure per capita. A multiple regression model was conducted and performance results of Lasso Regression, Random Forest Regression and Support Vector Machine Regression recorded when different hyperparameters are assigned. Lambda (λ) value for Lasso Regression, number of trees for Random Forest Regression, epsilon (ε) value for Support Vector Regression was determined as hyperparameters. Study results performed by using 'k' fold cross validation changed from 5 to 50, indicate the difference between machine learning regression results in terms of R², RMSE and MAE values that are statistically significant (p < 0.001). Study results reveal that Random Forest Regression (R² ˃ 0.7500, RMSE ≤ 0.6000 ve MAE ≤ 0.4000) outperforms other machine learning regression methods. It is highly advisable to use machine learning regression methods for modelling health expenditures. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=machine%20learning" title="machine learning">machine learning</a>, <a href="https://publications.waset.org/abstracts/search?q=lasso%20regression" title=" lasso regression"> lasso regression</a>, <a href="https://publications.waset.org/abstracts/search?q=random%20forest%20regression" title=" random forest regression"> random forest regression</a>, <a href="https://publications.waset.org/abstracts/search?q=support%20vector%20regression" title=" support vector regression"> support vector regression</a>, <a href="https://publications.waset.org/abstracts/search?q=hyperparameter%20tuning" title=" hyperparameter tuning"> hyperparameter tuning</a>, <a href="https://publications.waset.org/abstracts/search?q=health%20expenditure" title=" health expenditure"> health expenditure</a> </p> <a href="https://publications.waset.org/abstracts/97629/optimization-of-machine-learning-regression-results-an-application-on-health-expenditures" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/97629.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">226</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">3234</span> A Comparison of Smoothing Spline Method and Penalized Spline Regression Method Based on Nonparametric Regression Model</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Autcha%20Araveeporn">Autcha Araveeporn</a> </p> <p class="card-text"><strong>Abstract:</strong></p> This paper presents a study about a nonparametric regression model consisting of a smoothing spline method and a penalized spline regression method. We also compare the techniques used for estimation and prediction of nonparametric regression model. We tried both methods with crude oil prices in dollars per barrel and the Stock Exchange of Thailand (SET) index. According to the results, it is concluded that smoothing spline method performs better than that of penalized spline regression method. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=nonparametric%20regression%20model" title="nonparametric regression model">nonparametric regression model</a>, <a href="https://publications.waset.org/abstracts/search?q=penalized%20spline%20regression%20method" title=" penalized spline regression method"> penalized spline regression method</a>, <a href="https://publications.waset.org/abstracts/search?q=smoothing%20spline%20method" title=" smoothing spline method"> smoothing spline method</a>, <a href="https://publications.waset.org/abstracts/search?q=Stock%20Exchange%20of%20Thailand%20%28SET%29" title=" Stock Exchange of Thailand (SET)"> Stock Exchange of Thailand (SET)</a> </p> <a href="https://publications.waset.org/abstracts/2974/a-comparison-of-smoothing-spline-method-and-penalized-spline-regression-method-based-on-nonparametric-regression-model" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/2974.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">439</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">3233</span> The Labor Participation–Fertility Trade-off: The Case of the Philippines</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Daphne%20Ashley%20Sze">Daphne Ashley Sze</a>, <a href="https://publications.waset.org/abstracts/search?q=Kenneth%20Santos"> Kenneth Santos</a>, <a href="https://publications.waset.org/abstracts/search?q=Ariane%20Gabrielle%20Lim"> Ariane Gabrielle Lim</a> </p> <p class="card-text"><strong>Abstract:</strong></p> As women are now given more freedom and choice to pursue employment, the world’s over-all fertility has been decreasing mainly due to the shift in time allocation between working and child rearing. As such, we study the case of the Philippines, where there exists a decreasing fertility rate and increasing openness for women labor participation. We focused on the distinction between fertility and fecundity, the former being the manifestation of the latter and aim to trace and compare the effects of both fecundity and fertility to women’s employment status through the estimation of the reproduction function and multinomial logistic function. Findings suggest that the perception of women regarding employment opportunities in the Philippines links the negative relationship observed between fertility, fecundity and women’s employment status. Today, there has been a convergence in the traditional family roles of men and women, as both genders now have identical employment opportunities that continue to shape their preferences. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=multinomial%20logistic%20function" title="multinomial logistic function">multinomial logistic function</a>, <a href="https://publications.waset.org/abstracts/search?q=tobit" title=" tobit"> tobit</a>, <a href="https://publications.waset.org/abstracts/search?q=fertility" title=" fertility"> fertility</a>, <a href="https://publications.waset.org/abstracts/search?q=women%20employment%20status" title=" women employment status"> women employment status</a>, <a href="https://publications.waset.org/abstracts/search?q=fecundity" title=" fecundity"> fecundity</a> </p> <a href="https://publications.waset.org/abstracts/20416/the-labor-participation-fertility-trade-off-the-case-of-the-philippines" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/20416.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">606</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">3232</span> The Labor Participation-Fertility Trade-Off: Exploring Fecundity and Its Consequences to Women's Employment in the Philippines</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Ariane%20C.%20Lim">Ariane C. Lim</a>, <a href="https://publications.waset.org/abstracts/search?q=Daphne%20Ashley%20L.%20Sze"> Daphne Ashley L. Sze</a>, <a href="https://publications.waset.org/abstracts/search?q=Kenneth%20S.%20Santos"> Kenneth S. Santos</a> </p> <p class="card-text"><strong>Abstract:</strong></p> As women are now given more freedom and choice to pursue employment, the world’s over-all fertility has been decreasing mainly due to the shift in time allocation between working and child-rearing. As such, we study the case of the Philippines, where there exists a decreasing fertility rate and increasing openness for women labor participation. We focused on the distinction between fertility and fecundity, the former being the manifestation of the latter and aim to trace and compare the effects of both fecundity and fertility to women’s employment status through the estimation of the reproduction function and multinomial logistic function. Findings suggest that the perception of women regarding employment opportunities in the Philippines links the negative relationship observed between fertility, fecundity and women’s employment status. Today, there has been a convergence in the traditional family roles of men and women, as both genders now have identical employment opportunities that continue to shape their preferences. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=multinomial%20logistic%20function" title="multinomial logistic function">multinomial logistic function</a>, <a href="https://publications.waset.org/abstracts/search?q=tobit" title=" tobit"> tobit</a>, <a href="https://publications.waset.org/abstracts/search?q=fertility" title=" fertility"> fertility</a>, <a href="https://publications.waset.org/abstracts/search?q=women%20employment%20status" title=" women employment status"> women employment status</a>, <a href="https://publications.waset.org/abstracts/search?q=fecundity" title=" fecundity "> fecundity </a> </p> <a href="https://publications.waset.org/abstracts/21518/the-labor-participation-fertility-trade-off-exploring-fecundity-and-its-consequences-to-womens-employment-in-the-philippines" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/21518.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">629</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">3231</span> Orthogonal Regression for Nonparametric Estimation of Errors-In-Variables Models</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Anastasiia%20Yu.%20Timofeeva">Anastasiia Yu. Timofeeva</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Two new algorithms for nonparametric estimation of errors-in-variables models are proposed. The first algorithm is based on penalized regression spline. The spline is represented as a piecewise-linear function and for each linear portion orthogonal regression is estimated. This algorithm is iterative. The second algorithm involves locally weighted regression estimation. When the independent variable is measured with error such estimation is a complex nonlinear optimization problem. The simulation results have shown the advantage of the second algorithm under the assumption that true smoothing parameters values are known. Nevertheless the use of some indexes of fit to smoothing parameters selection gives the similar results and has an oversmoothing effect. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=grade%20point%20average" title="grade point average">grade point average</a>, <a href="https://publications.waset.org/abstracts/search?q=orthogonal%20regression" title=" orthogonal regression"> orthogonal regression</a>, <a href="https://publications.waset.org/abstracts/search?q=penalized%20regression%20spline" title=" penalized regression spline"> penalized regression spline</a>, <a href="https://publications.waset.org/abstracts/search?q=locally%20weighted%20regression" title=" locally weighted regression"> locally weighted regression</a> </p> <a href="https://publications.waset.org/abstracts/11927/orthogonal-regression-for-nonparametric-estimation-of-errors-in-variables-models" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/11927.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">416</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">3230</span> Indigenous Adaptation Strategies for Climate Change: Small Farmers’ Options for Sustainable Crop Farming in South-Western Nigeria</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Emmanuel%20Olasope%20Bamigboye">Emmanuel Olasope Bamigboye</a>, <a href="https://publications.waset.org/abstracts/search?q=Ismail%20Oladeji%20Oladosu"> Ismail Oladeji Oladosu</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Local people of south-western Nigeria like in other climes, continue to be confronted with the vagaries of changing environments. Through the modification of existing practice and shifting resource base, their strategies for coping with change have enabled them to successfully negotiate the shifts in climate change and the environment. This article analyses indigenous adaptation strategies for climate change with a view to enhancing sustainable crop farming in south –western Nigeria. Multi-stage sampling procedure was used to select 340 respondents from the two major ecological zones (Forest and Derived Savannah) for good geographical spread. The article draws on mixed methods of qualitative research, literature review, field observations, informal interview and multinomial logit regression to capture choice probabilities across the various options of climate change adaptation options among arable crop farmers. The study revealed that most 85.0% of the arable crop farmers were males. It also showed that the use of local climate change adaptation strategies had no relationship with the educational level of the respondents as 77.3% had educational experiences at varying levels. Furthermore, the findings showed that seven local adaptation strategies were commonly utilized by arable crop farmers. Nonetheless, crop diversification, consultation with rainmakers and involvement in non-agricultural ventures were prioritized in the order of 1-3, respectively. Also, multinomial logit analysis result showed that at p ≤ 0.05 level of significance, household size (P<0.08), sex (p<0.06), access to loan(p<0.16), age(p<0.07), educational level (P<0.17) and functional extension contact (P<0.28) were all important in explaining the indigenous climate change adaptation utilized by the arable crops farmers in south-western Nigeria. The study concluded that all the identified local adaptation strategies need to be integrated into the development process for sustainable climate change adaptation. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=crop%20diversification" title="crop diversification">crop diversification</a>, <a href="https://publications.waset.org/abstracts/search?q=climate%20change" title=" climate change"> climate change</a>, <a href="https://publications.waset.org/abstracts/search?q=adaptation%20option" title=" adaptation option"> adaptation option</a>, <a href="https://publications.waset.org/abstracts/search?q=sustainable" title=" sustainable"> sustainable</a>, <a href="https://publications.waset.org/abstracts/search?q=small%20farmers" title=" small farmers"> small farmers</a> </p> <a href="https://publications.waset.org/abstracts/58273/indigenous-adaptation-strategies-for-climate-change-small-farmers-options-for-sustainable-crop-farming-in-south-western-nigeria" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/58273.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">297</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">3229</span> A Learning-Based EM Mixture Regression Algorithm</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Yi-Cheng%20Tian">Yi-Cheng Tian</a>, <a href="https://publications.waset.org/abstracts/search?q=Miin-Shen%20Yang"> Miin-Shen Yang</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The mixture likelihood approach to clustering is a popular clustering method where the expectation and maximization (EM) algorithm is the most used mixture likelihood method. In the literature, the EM algorithm had been used for mixture regression models. However, these EM mixture regression algorithms are sensitive to initial values with a priori number of clusters. In this paper, to resolve these drawbacks, we construct a learning-based schema for the EM mixture regression algorithm such that it is free of initializations and can automatically obtain an approximately optimal number of clusters. Some numerical examples and comparisons demonstrate the superiority and usefulness of the proposed learning-based EM mixture regression algorithm. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=clustering" title="clustering">clustering</a>, <a href="https://publications.waset.org/abstracts/search?q=EM%20algorithm" title=" EM algorithm"> EM algorithm</a>, <a href="https://publications.waset.org/abstracts/search?q=Gaussian%20mixture%20model" title=" Gaussian mixture model"> Gaussian mixture model</a>, <a href="https://publications.waset.org/abstracts/search?q=mixture%20regression%20model" title=" mixture regression model"> mixture regression model</a> </p> <a href="https://publications.waset.org/abstracts/25163/a-learning-based-em-mixture-regression-algorithm" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/25163.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">510</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">3228</span> Fruits and Vegetable Consumers' Behaviour towards Organised Retailers: Evidence from India </h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=K.%20B.%20Ramappa">K. B. Ramappa</a>, <a href="https://publications.waset.org/abstracts/search?q=A.%20V.%20Manjunatha"> A. V. Manjunatha</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Consumerism in India is witnessing unprecedented growth driven by favourable demographics, rising young and working population, rising income levels, urbanization and growing brand orientation. In addition, the increasing level of awareness on health, hygiene and quality has made the consumers to think on the fairly traded goods and brands. This has made retailing extremely important to everyone because without retailers’ consumers would not have access to day-to-day products. The increased competition among different retailers has contributed significantly towards rising consumer awareness on quality products and brand loyalty. Many existing empirical studies have mainly focused on net saving of consumers at organised retail via-a-vis unorganised retail shops. In this article, authors have analysed the Bangalore consumers' attitudes towards buying of fruits and vegetables and their choice of retail outlets. The primary data was collected from 100 consumers belonging to the Bangalore City during October 2014. Sample consumers buying at supermarkets, convenience stores and hypermarkets were purposively selected. The collected data was analyzed using descriptive statistics and multinomial logit model. It was found that among all variables, quality and prices were major accountable factors for buying fruits and vegetables at organized retail shops. The empirical result of multinomial logit model reveals that annual net income was positively associated with the Big Bazar and Food World consumers and negatively associated with the Reliance Fresh, More and Niligiris consumers, as compared with the HOPCOMS consumers. Per month expenditure on fruits and vegetables was positively and age of the consumer was negatively related to the consumers’ choice of buying at modern retail markets. Consumers were willing to buy at modern retail outlets irrespective of the distance. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=organized%20retailers" title="organized retailers">organized retailers</a>, <a href="https://publications.waset.org/abstracts/search?q=consumers%27%20attitude" title=" consumers' attitude"> consumers' attitude</a>, <a href="https://publications.waset.org/abstracts/search?q=consumers%27%20preference" title=" consumers' preference"> consumers' preference</a>, <a href="https://publications.waset.org/abstracts/search?q=fruits" title=" fruits"> fruits</a>, <a href="https://publications.waset.org/abstracts/search?q=vegetables" title=" vegetables"> vegetables</a>, <a href="https://publications.waset.org/abstracts/search?q=multinomial%20logit" title=" multinomial logit"> multinomial logit</a>, <a href="https://publications.waset.org/abstracts/search?q=Bangalore" title=" Bangalore "> Bangalore </a> </p> <a href="https://publications.waset.org/abstracts/23825/fruits-and-vegetable-consumers-behaviour-towards-organised-retailers-evidence-from-india" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/23825.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">413</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">3227</span> Prediction of Energy Storage Areas for Static Photovoltaic System Using Irradiation and Regression Modelling</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Kisan%20Sarda">Kisan Sarda</a>, <a href="https://publications.waset.org/abstracts/search?q=Bhavika%20Shingote"> Bhavika Shingote</a> </p> <p class="card-text"><strong>Abstract:</strong></p> This paper aims to evaluate regression modelling for prediction of Energy storage of solar photovoltaic (PV) system using Semi parametric regression techniques because there are some parameters which are known while there are some unknown parameters like humidity, dust etc. Here irradiation of solar energy is different for different places on the basis of Latitudes, so by finding out areas which give more storage we can implement PV systems at those places and our need of energy will be fulfilled. This regression modelling is done for daily, monthly and seasonal prediction of solar energy storage. In this, we have used R modules for designing the algorithm. This algorithm will give the best comparative results than other regression models for the solar PV cell energy storage. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=semi%20parametric%20regression" title="semi parametric regression">semi parametric regression</a>, <a href="https://publications.waset.org/abstracts/search?q=photovoltaic%20%28PV%29%20system" title=" photovoltaic (PV) system"> photovoltaic (PV) system</a>, <a href="https://publications.waset.org/abstracts/search?q=regression%20modelling" title=" regression modelling"> regression modelling</a>, <a href="https://publications.waset.org/abstracts/search?q=irradiation" title=" irradiation"> irradiation</a> </p> <a href="https://publications.waset.org/abstracts/65373/prediction-of-energy-storage-areas-for-static-photovoltaic-system-using-irradiation-and-regression-modelling" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/65373.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">381</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">3226</span> Investigating Income Diversification Strategies into Off-Farm Activities Among Rural Households in Ethiopia</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Kibret%20Berhanu%20Getinet">Kibret Berhanu Getinet</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Off-farm income diversification by farm rural households has gained the attention of researchers and policymakers due to the fact that agriculture failed to meet the needs of people in developing countries like Ethiopia. The objective of this study was to investigate income diversification strategies into off-farm activities among rural households in Hawassa Zuria Woreda, Sidama National Regional State, Ethiopia. The study used primary and secondary data sources for the primary data collection questionnaire employed as a data collection instrument. A multistage sampling technique was used to collect data from a total of 197 sample households from four kebeles of the study area. Descriptive statistics, as well as econometrics methods of data analysis, were employed. The descriptive statistics result indicates that the majority of sample rural households (68.53 %) have engaged in off-farm income diversification activities while the remaining 31.47% of households did not participate in the diversification in the study area. The choice of participants among the strategies indicates that 6.60% of respondents participated in off-farm wage employment, 30.46% participated in off-farm self-employment, and about 31.47% of them participated in both off-farm wage employment. The study revealed that the share of off-farm income in total annual earnings of households was about 48.457%, and thus, the off-farm diversification significantly contributes to the rural household income. Moreover, binary and multinomial logistic regression models were employed to identify factors that affect the participation and the choices of the off-farm income diversification strategies, respectively. The binary logit model result indicated that agro-ecological zone, education status of the households, available technical skills of the household, household saving, total livestock owned by the households, access to electricity, road access and being married of household head were significant and positively affected the chance of diversification in off-farm activities while the on-farm income of households is negatively affected the chance of diversification. Similarly, the multinomial logistic regression model estimate revealed that agroecological zone, on-farm income, available technical skills, household savings, and access to electricity are positively related and significantly influenced the household’s choice of employment into off-farm wage employment. The off-farm self-employment diversification choice is significantly influenced by on-farm income, available technical skills, household savings, total livestock owned, and access to electricity. Moreover, the result showed that the factors that affect the choice of farm households to engage in both off-farm wage and self-employment are ecological zone, education status, on-farm income, available technical skills, household own saving, market access, total livestock owned, access to electricity and road access. Thus, due attention should be given to addressing the demographic, socio-economic, and institutional constraints to strengthen off-farm income diversification strategies to improve the income of rural households. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=off-farm" title="off-farm">off-farm</a>, <a href="https://publications.waset.org/abstracts/search?q=incoem" title=" incoem"> incoem</a>, <a href="https://publications.waset.org/abstracts/search?q=diversification" title=" diversification"> diversification</a>, <a href="https://publications.waset.org/abstracts/search?q=logit%20model" title=" logit model"> logit model</a> </p> <a href="https://publications.waset.org/abstracts/182343/investigating-income-diversification-strategies-into-off-farm-activities-among-rural-households-in-ethiopia" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/182343.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">53</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">3225</span> The Impact of International Financial Reporting Standards (IFRS) Adoption on Performance’s Measure: A Study of UK Companies</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Javad%20Izadi">Javad Izadi</a>, <a href="https://publications.waset.org/abstracts/search?q=Sahar%20Majioud"> Sahar Majioud</a> </p> <p class="card-text"><strong>Abstract:</strong></p> This study presents an approach of assessing the choice of performance measures of companies in the United Kingdom after the application of IFRS in 2005. The aim of this study is to investigate the effects of IFRS on the choice of performance evaluation methods for UK companies. We analyse through an econometric model the relationship of the dependent variable, the firm’s performance, which is a nominal variable with the independent ones. Independent variables are split into two main groups: the first one is the group of accounting-based measures: Earning per share, return on assets and return on equities. The second one is the group of market-based measures: market value of property plant and equipment, research and development, sales growth, market to book value, leverage, segment and size of companies. Concerning the regression used, it is a multinomial logistic regression performed on a sample of 130 UK listed companies. Our finding shows after IFRS adoption, and companies give more importance to some variables such as return on equities and sales growth to assess their performance, whereas the return on assets and market to book value ratio does not have as much importance as before IFRS in evaluating the performance of companies. Also, there are some variables that have no impact on the performance measures anymore, such as earning per share. This article finding is empirically important for business in subjects related to IFRS and companies’ performance measurement. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=performance%E2%80%99s%20Measure" title="performance’s Measure">performance’s Measure</a>, <a href="https://publications.waset.org/abstracts/search?q=nominal%20variable" title=" nominal variable"> nominal variable</a>, <a href="https://publications.waset.org/abstracts/search?q=econometric%20model" title=" econometric model"> econometric model</a>, <a href="https://publications.waset.org/abstracts/search?q=evaluation%20methods" title=" evaluation methods"> evaluation methods</a> </p> <a href="https://publications.waset.org/abstracts/146743/the-impact-of-international-financial-reporting-standards-ifrs-adoption-on-performances-measure-a-study-of-uk-companies" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/146743.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">138</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">3224</span> New Segmentation of Piecewise Linear Regression Models Using Reversible Jump MCMC Algorithm</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Suparman">Suparman</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Piecewise linear regression models are very flexible models for modeling the data. If the piecewise linear regression models are matched against the data, then the parameters are generally not known. This paper studies the problem of parameter estimation of piecewise linear regression models. The method used to estimate the parameters of picewise linear regression models is Bayesian method. But the Bayes estimator can not be found analytically. To overcome these problems, the reversible jump MCMC algorithm is proposed. Reversible jump MCMC algorithm generates the Markov chain converges to the limit distribution of the posterior distribution of the parameters of picewise linear regression models. The resulting Markov chain is used to calculate the Bayes estimator for the parameters of picewise linear regression models. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=regression" title="regression">regression</a>, <a href="https://publications.waset.org/abstracts/search?q=piecewise" title=" piecewise"> piecewise</a>, <a href="https://publications.waset.org/abstracts/search?q=Bayesian" title=" Bayesian"> Bayesian</a>, <a href="https://publications.waset.org/abstracts/search?q=reversible%20Jump%20MCMC" title=" reversible Jump MCMC"> reversible Jump MCMC</a> </p> <a href="https://publications.waset.org/abstracts/31651/new-segmentation-of-piecewise-linear-regression-models-using-reversible-jump-mcmc-algorithm" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/31651.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">521</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">3223</span> Application Difference between Cox and Logistic Regression Models</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Idrissa%20Kayijuka">Idrissa Kayijuka</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The logistic regression and Cox regression models (proportional hazard model) at present are being employed in the analysis of prospective epidemiologic research looking into risk factors in their application on chronic diseases. However, a theoretical relationship between the two models has been studied. By definition, Cox regression model also called Cox proportional hazard model is a procedure that is used in modeling data regarding time leading up to an event where censored cases exist. Whereas the Logistic regression model is mostly applicable in cases where the independent variables consist of numerical as well as nominal values while the resultant variable is binary (dichotomous). Arguments and findings of many researchers focused on the overview of Cox and Logistic regression models and their different applications in different areas. In this work, the analysis is done on secondary data whose source is SPSS exercise data on BREAST CANCER with a sample size of 1121 women where the main objective is to show the application difference between Cox regression model and logistic regression model based on factors that cause women to die due to breast cancer. Thus we did some analysis manually i.e. on lymph nodes status, and SPSS software helped to analyze the mentioned data. This study found out that there is an application difference between Cox and Logistic regression models which is Cox regression model is used if one wishes to analyze data which also include the follow-up time whereas Logistic regression model analyzes data without follow-up-time. Also, they have measurements of association which is different: hazard ratio and odds ratio for Cox and logistic regression models respectively. A similarity between the two models is that they are both applicable in the prediction of the upshot of a categorical variable i.e. a variable that can accommodate only a restricted number of categories. In conclusion, Cox regression model differs from logistic regression by assessing a rate instead of proportion. The two models can be applied in many other researches since they are suitable methods for analyzing data but the more recommended is the Cox, regression model. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=logistic%20regression%20model" title="logistic regression model">logistic regression model</a>, <a href="https://publications.waset.org/abstracts/search?q=Cox%20regression%20model" title=" Cox regression model"> Cox regression model</a>, <a href="https://publications.waset.org/abstracts/search?q=survival%20analysis" title=" survival analysis"> survival analysis</a>, <a href="https://publications.waset.org/abstracts/search?q=hazard%20ratio" title=" hazard ratio"> hazard ratio</a> </p> <a href="https://publications.waset.org/abstracts/66111/application-difference-between-cox-and-logistic-regression-models" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/66111.pdf" target="_blank" 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