Open AccessA Comparative Study of Goodness-of-Fit Tests for the Laplace Distribution
Author(s) -
Apostolos Batsidis,
Polychronis Εconomou,
Shaul K. BarLev
Publication year - 2022
Publication title -
österreichische zeitschrift für statistik
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.342
H-Index - 9
ISSN - 1026-597X
DOI - 10.17713/ajs.v51i2.1251
Subject(s) - goodness of fit , laplace distribution , laplace transform , mathematics , monte carlo method , anderson–darling test , distribution (mathematics) , statistics , statistical physics , statistical hypothesis testing , kolmogorov–smirnov test , mathematical analysis , physics
The Laplace distribution is one of the earliest distributions in probability theory and is a frequently used distribution in many fields. Consequently, various goodness-of-fit tests for the Laplace distribution have been thoroughly derived in theliterature. The purpose of this paper is to carry out a comparative study of these tests as well as a new one we develop. Power comparisons of all such tests are performed via Monte Carlo simulations of sample data generatedfrom twenty seven alternatives distributions. Despite the fact that no single test was found to be most powerful in all situations, several useful recommendations however are made.