Testing for the mixture hypothesis of conditional geometric and exponential distributions

Jin Seo Cho, Jin Seok Park, Sang Woo Park

Research output: Contribution to journalArticle

Abstract

This study examines the mixture hypothesis of conditional geometric distributions using a likelihood ratio (LR) test statistic based on that used for unconditional geometric distributions. As such, we derive the null limit distribution of the LR test statistic and examine its power performance. In addition, we examine the interrelationship between the LR test statistics used to test the geometric and exponential mixture hypotheses. We also examine the performance of the LR test statistics under various conditions and confirm the main claims of the study using Monte Carlo simulations. ecosystems.

Original languageEnglish
Pages (from-to)1-27
Number of pages27
JournalJournal of Economic Theory and Econometrics
Volume29
Issue number2
Publication statusPublished - 2018 Jun 1

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Likelihood ratio test
Test statistic
Exponential distribution
Geometric distribution
Testing
Ecosystem
Monte Carlo simulation
Interrelationship
Limit distribution

All Science Journal Classification (ASJC) codes

  • Economics and Econometrics

Cite this

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Testing for the mixture hypothesis of conditional geometric and exponential distributions. / Cho, Jin Seo; Park, Jin Seok; Park, Sang Woo.

In: Journal of Economic Theory and Econometrics, Vol. 29, No. 2, 01.06.2018, p. 1-27.

Research output: Contribution to journalArticle

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