Document Type

Journal Article

Department/Unit

Department of Mathematics

Title

Testing for positive expectation dependence

Language

English

Abstract

© 2014, The Institute of Statistical Mathematics, Tokyo.In this paper, hypothesis testing for positive first-degree and higher-degree expectation dependence is investigated. Some tests of Kolmogorov–Smirnov type are constructed, which are shown to control type I error well and to be consistent against global alternative hypothesis. Further, the tests can also detect local alternative hypotheses distinct from the null hypothesis at a rate as close to the square root of the sample size as possible, which is the fastest possible rate in hypothesis testing. A nonparametric Monte Carlo test procedure is applied to implement the new tests because both sampling and limiting null distributions are not tractable. Simulation studies and a real data analysis are carried out to illustrate the performances of the new tests.

Keywords

Expectation dependence, Nonparametric Monte Carlo, Test of Kolmogorov–Smirnov type

Publication Date

2016

Source Publication Title

Annals of the Institute of Statistical Mathematics

Volume

68

Issue

1

Start Page

135

End Page

153

Publisher

Springer Verlag

DOI

10.1007/s10463-014-0492-7

Link to Publisher's Edition

http://dx.doi.org/10.1007/s10463-014-0492-7

ISSN (print)

00203157

ISSN (electronic)

15729052

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