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Article

Title: Rank tests in regression model based on minimum distance estimates (English)
Author: Navrátil, Radim
Language: English
Journal: Kybernetika
ISSN: 0023-5954 (print)
ISSN: 1805-949X (online)
Volume: 51
Issue: 6
Year: 2015
Pages: 909-922
Summary lang: English
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Category: math
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Summary: In this paper a new rank test in a linear regression model is introduced. The test statistic is based on a certain minimum distance estimator, however, unlike classical rank tests in regression it is not a simple linear rank statistic. Its exact distribution under the null hypothesis is derived, and further, the asymptotic distribution both under the null hypothesis and the local alternative is investigated. It is shown that the proposed test is applicable in measurement error models. Finally, a simulation study is conducted to show a good performance of the test. It has, in some situations, a greater power than the widely used Wilcoxon rank test. (English)
Keyword: measurement errors
Keyword: minimum distance estimates
Keyword: rank tests
MSC: 62G10
MSC: 62J05
idZBL: Zbl 06537787
idMR: MR3453677
DOI: 10.14736/kyb-2015-6-0909
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Date available: 2016-01-21T18:12:27Z
Last updated: 2018-01-10
Stable URL: http://hdl.handle.net/10338.dmlcz/144815
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