Comparison of Bayesian and Regression Schemes to Model Public Health Services

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Regression Schemes to Model Public Health Services</title> <meta name="description" content="Comparison of Bayesian and Regression Schemes to Model Public Health Services"> <meta name="keywords" content="Bayesian probability, cohorts, data frames, regression, services, prediction."> <meta name="viewport" content="width=device-width, initial-scale=1, minimum-scale=1, maximum-scale=1, user-scalable=no"> <meta charset="utf-8"> <meta name="citation_title" content="Comparison of Bayesian and Regression Schemes to Model Public Health Services"> <meta name="citation_author" content="Sotirios Raptis"> <meta name="citation_publication_date" content="2023/08/16"> <meta name="citation_journal_title" content="International Journal of Mathematical and Computational Sciences"> <meta name="citation_volume" content="17"> <meta name="citation_issue" content="8"> <meta name="citation_firstpage" content="94"> <meta name="citation_lastpage" content="107"> <meta name="citation_pdf_url" 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(AR/LR) can predict different sources of data using priors or other data, and can link social service demands in cohorts, while their consideration in isolation (self-prediction) may lead to service misuse ignoring the context. The paper advocates that BR with Binomial (BD), or Normal (ND) models or raw data (.D) as probabilistic updates can be compared to AR/LR to link services in Scotland and reduce cost by sharing healthcare (HC) resources. Clustering, cross-correlation, along with BR, LR, AR can better predict demand. Insurance companies and policymakers can link such services, and examples include those offered to the elderly, and low-income people, smoking-related services linked to mental health services, or epidemiological weight in children. 22 service packs are used that are published by Public Health Services (PHS) Scotland and Scottish Government (SG) from 1981 to 2019, broken into 110 year series (factors), joined using LR, AR, BR. The Primary component analysis found 11 significant factors, while C-Means (CM) clustering gave five major clusters.</p> <iframe src="https://publications.waset.org/10013217.pdf" style="width:100%; height:400px;" frameborder="0"></iframe> <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/search?q=Bayesian%20probability" title="Bayesian probability">Bayesian probability</a>, <a href="https://publications.waset.org/search?q=cohorts" title=" cohorts"> cohorts</a>, <a href="https://publications.waset.org/search?q=data%20frames" title=" data frames"> data frames</a>, <a href="https://publications.waset.org/search?q=regression" title=" regression"> regression</a>, <a href="https://publications.waset.org/search?q=services" title=" services"> services</a>, <a href="https://publications.waset.org/search?q=prediction." title=" prediction."> prediction.</a> </p> <a href="https://publications.waset.org/10013217/comparison-of-bayesian-and-regression-schemes-to-model-public-health-services" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/10013217/apa" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">APA</a> <a href="https://publications.waset.org/10013217/bibtex" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">BibTeX</a> <a href="https://publications.waset.org/10013217/chicago" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">Chicago</a> <a href="https://publications.waset.org/10013217/endnote" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">EndNote</a> <a href="https://publications.waset.org/10013217/harvard" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">Harvard</a> <a href="https://publications.waset.org/10013217/json" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">JSON</a> <a href="https://publications.waset.org/10013217/mla" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">MLA</a> <a href="https://publications.waset.org/10013217/ris" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">RIS</a> <a href="https://publications.waset.org/10013217/xml" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">XML</a> <a href="https://publications.waset.org/10013217/iso690" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">ISO 690</a> <a href="https://publications.waset.org/10013217.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">225</span> </span> <p class="card-text"><strong>References:</strong></p> <br>[1] ByXu., HRISTINA PASHOVA† AND PATRICK J. 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Comparison of Bayesian and Regression Schemes to Model Public Health Services