A Comparative Study of Goodness-of-Fit Tests for the Laplace Distribution

Apostolos Batsidis; Polychronis Economou; Shaul K. Bar-Lev

doi:10.17713/ajs.v51i2.1251

A Comparative Study of Goodness-of-Fit Tests for the Laplace Distribution

Apostolos Batsidis, Polychronis Economou, Shaul K. Bar-Lev

Research output: Contribution to journal › Article › peer-review

Abstract

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 the literature. 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 generated from 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.

Original language	English
Pages (from-to)	91-123
Number of pages	33
Journal	Austrian Journal of Statistics
Volume	51
Issue number	2
DOIs	https://doi.org/10.17713/ajs.v51i2.1251
State	Published - 25 Jan 2022
Externally published	Yes

Bibliographical note

Publisher Copyright:
© 2022, Austrian Statistical Society. All rights reserved.

Keywords

Goodness-of-fit
Laplace distribution
Monte Carlo study

ASJC Scopus subject areas

Statistics and Probability
Statistics, Probability and Uncertainty
Applied Mathematics

Access to Document

10.17713/ajs.v51i2.1251

Cite this

@article{791ae461ed6d41d7a48009196be7342f,

title = "A Comparative Study of Goodness-of-Fit Tests for the Laplace Distribution",

abstract = "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 the literature. 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 generated from 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.",

keywords = "Goodness-of-fit, Laplace distribution, Monte Carlo study",

author = "Apostolos Batsidis and Polychronis Economou and Bar-Lev, {Shaul K.}",

year = "2022",

month = jan,

day = "25",

doi = "10.17713/ajs.v51i2.1251",

language = "English",

volume = "51",

pages = "91--123",

journal = "Austrian Journal of Statistics",

issn = "1026-597X",

publisher = "Austrian Society for Statistics",

number = "2",

}

TY - JOUR

T1 - A Comparative Study of Goodness-of-Fit Tests for the Laplace Distribution

AU - Batsidis, Apostolos

AU - Economou, Polychronis

AU - Bar-Lev, Shaul K.

PY - 2022/1/25

Y1 - 2022/1/25

N2 - 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 the literature. 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 generated from 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.

AB - 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 the literature. 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 generated from 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.

KW - Goodness-of-fit

KW - Laplace distribution

KW - Monte Carlo study

UR - http://www.scopus.com/inward/record.url?scp=85124505211&partnerID=8YFLogxK

U2 - 10.17713/ajs.v51i2.1251

DO - 10.17713/ajs.v51i2.1251

M3 - Article

AN - SCOPUS:85124505211

SN - 1026-597X

VL - 51

SP - 91

EP - 123

JO - Austrian Journal of Statistics

JF - Austrian Journal of Statistics

IS - 2

ER -

A Comparative Study of Goodness-of-Fit Tests for the Laplace Distribution

Abstract

Bibliographical note

Keywords

ASJC Scopus subject areas

Access to Document

Other files and links

Fingerprint

Cite this