{"title":"Confidence Intervals for Double Exponential Distribution: A Simulation Approach","authors":"M. Alrasheedi","volume":61,"journal":"International Journal of Physical and Mathematical Sciences","pagesStart":84,"pagesEnd":89,"ISSN":"1307-6892","URL":"https:\/\/publications.waset.org\/pdf\/8809","abstract":"The double exponential model (DEM), or Laplace\ndistribution, is used in various disciplines. However, there are issues\nrelated to the construction of confidence intervals (CI), when using\nthe distribution.In this paper, the properties of DEM are considered\nwith intention of constructing CI based on simulated data. The\nanalysis of pivotal equations for the models here in comparisons with\npivotal equations for normal distribution are performed, and the\nresults obtained from simulation data are presented.","references":"[1] S. Kotz, T. Kozubowski, K. Podgorski, The Laplace Distribution and\nGeneralizations, Birkhauser Boston, 2001, Ch. 2-4.\n[2] N. Johnson, S. Kotz, N. Balakrishnan, Continuous Univariate\nDistributions, Vol. 2, Wiley-Interscience, 1995, Ch. 24 .\n[3] Y. R. Gel, \"Test of fit for a Laplace distribution against heavier tailed\nalternatives\", Computational Statistics and Data Analysis, Vol. 54, no. 4,\npp. 958-965, 2010.\n[4] N. Ekstrand, B. Smeets, \"Weighting of double exponential distributed\ndata in lossless image compression\", Lund University. Data compression\nconference, March 30-April 01, 1998.\n[5] J. Rice, Mathematical statistics and data analysis, 3rd edition, Thomson\nBrooks\/Cole, 2007, p. 275-280.","publisher":"World Academy of Science, Engineering and Technology","index":"Open Science Index 61, 2012"}