Tests for skewness parameter of skew log Laplace distribution

Author:

Khandeparkar Pradnya1,Dixit Vaijayanti2

Affiliation:

1. Nilkamal School of Mathematics, Applied Statistics and Analytics, SVKM’s NMIMS Deemed to be University, Mumbai, India

2. Department of Statistics, University of Mumbai, Mumbai, India

Abstract

Laplace probability density function with additional shape parameter that regulates the degree of skewness is a skew Laplace distribution. The various forms of skew Laplace distribution are found in the literature, the distributions defined by Mc Gill (1962), Holla and Bhattacharya (1968), Lingappaiah (1988), Fernandez and Steel (1998). The skew log Laplace distribution is the probability distribution of a random variable whose logarithm follows a skew Laplace distribution. In this paper, the classical optimum tests for skewness parameter of skew log Laplace distribution (SLLD) derived from Lingappaiah (1988) distribution are discussed. Uniformly most powerful test, uniformly most powerful unbiased test and Wald’s sequential probability ratio test for skewness parameter are compared. The exact likelihood ratio test and Neyman structure test for testing skewness parameter when scale parameter is known are derived. Finally, the underreported income of Road Transport Company is analysed on the basis of the tests derived in this paper.

Publisher

IOS Press

Subject

Applied Mathematics,Modeling and Simulation,Statistics and Probability

Reference7 articles.

1. On Bayesian modeling of fat tails and skewness;Fernandez;J Am Stat Assoc,1998

2. On the estimation of the Pareto Law from under-reported data;Hartley;Journal of Econometrics,1974

3. On a compound Gaussian distribution;Holla;Ann Inst Stat Math,1968

4. Log-Laplace distributions;Kozubowski;International Mathematical Journal,2003

5. Characterization of the Pareto distribution through a model of underreported incomes;Krishnaji;Econometrica,1970

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3