A new test for two-sample location problem based on empirical distribution function

Sunil Mathur, D. M. Sakate

Research output: Contribution to journalArticle

1 Citation (Scopus)

Abstract

We propose a new test for testing the equality of location parameter of two populations based on empirical distribution function (ECDF). The test statistics is obtained as a power divergence between two ECDFs. The test is shown to be distribution free, and its null distribution is obtained. We conducted empirical power comparison of the proposed test with several other available tests in the literature. We found that the proposed test performs better than its competitors considered here under several population structures. We also used two real datasets to illustrate the procedure.

Original languageEnglish (US)
Pages (from-to)12345-12355
Number of pages11
JournalCommunications in Statistics - Theory and Methods
Volume46
Issue number24
DOIs
StatePublished - Dec 17 2017

Fingerprint

Two-sample Problem
Empirical Distribution Function
Location Problem
Power Divergence
Power Comparison
Population Structure
Distribution-free
Location Parameter
Null Distribution
Test Statistic
Equality
Testing

Keywords

  • Power divergence
  • Wilcoxon's test
  • distribution free test
  • power

ASJC Scopus subject areas

  • Statistics and Probability

Cite this

A new test for two-sample location problem based on empirical distribution function. / Mathur, Sunil; Sakate, D. M.

In: Communications in Statistics - Theory and Methods, Vol. 46, No. 24, 17.12.2017, p. 12345-12355.

Research output: Contribution to journalArticle

@article{7e9294cf87fe4041be4e428691452c4c,
title = "A new test for two-sample location problem based on empirical distribution function",
abstract = "We propose a new test for testing the equality of location parameter of two populations based on empirical distribution function (ECDF). The test statistics is obtained as a power divergence between two ECDFs. The test is shown to be distribution free, and its null distribution is obtained. We conducted empirical power comparison of the proposed test with several other available tests in the literature. We found that the proposed test performs better than its competitors considered here under several population structures. We also used two real datasets to illustrate the procedure.",
keywords = "Power divergence, Wilcoxon's test, distribution free test, power",
author = "Sunil Mathur and Sakate, {D. M.}",
year = "2017",
month = "12",
day = "17",
doi = "10.1080/03610926.2017.1295158",
language = "English (US)",
volume = "46",
pages = "12345--12355",
journal = "Communications in Statistics - Theory and Methods",
issn = "0361-0926",
publisher = "Taylor and Francis Ltd.",
number = "24",

}

TY - JOUR

T1 - A new test for two-sample location problem based on empirical distribution function

AU - Mathur, Sunil

AU - Sakate, D. M.

PY - 2017/12/17

Y1 - 2017/12/17

N2 - We propose a new test for testing the equality of location parameter of two populations based on empirical distribution function (ECDF). The test statistics is obtained as a power divergence between two ECDFs. The test is shown to be distribution free, and its null distribution is obtained. We conducted empirical power comparison of the proposed test with several other available tests in the literature. We found that the proposed test performs better than its competitors considered here under several population structures. We also used two real datasets to illustrate the procedure.

AB - We propose a new test for testing the equality of location parameter of two populations based on empirical distribution function (ECDF). The test statistics is obtained as a power divergence between two ECDFs. The test is shown to be distribution free, and its null distribution is obtained. We conducted empirical power comparison of the proposed test with several other available tests in the literature. We found that the proposed test performs better than its competitors considered here under several population structures. We also used two real datasets to illustrate the procedure.

KW - Power divergence

KW - Wilcoxon's test

KW - distribution free test

KW - power

UR - http://www.scopus.com/inward/record.url?scp=85028768205&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=85028768205&partnerID=8YFLogxK

U2 - 10.1080/03610926.2017.1295158

DO - 10.1080/03610926.2017.1295158

M3 - Article

VL - 46

SP - 12345

EP - 12355

JO - Communications in Statistics - Theory and Methods

JF - Communications in Statistics - Theory and Methods

SN - 0361-0926

IS - 24

ER -