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image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Canadian Journal of ...arrow_drop_down
image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao
Canadian Journal of Statistics
Article . 2011 . Peer-reviewed
License: Wiley Online Library User Agreement
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image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao
zbMATH Open
Article . 2011
Data sources: zbMATH Open
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Tuning the EM‐test for finite mixture models

Tuning the EM-test for finite mixture models
Authors: Chen, Jiahua; Li, Pengfei;

Tuning the EM‐test for finite mixture models

Abstract

AbstractThere has been rapid progress in developing effective and easy‐to‐use tests of the order of a finite mixture model. The EM‐test is the latest to join the rank. It has a relatively simple limiting distribution and enjoys broad applicability. Based on asymptotic theory, the P‐value of the EM‐test is approximated via its limiting distribution. The built‐in tuning parameter has an important influence on the approximation precision. Thus, choosing an appropriate value for this parameter is important for fully realizing the advantages of the EM‐test. In this article, we develop a novel computer‐experiment approach to address this issue. Through designed experiments, we derive a number of empirical formulas for the tuning parameter. Extensive validation simulation shows that these formulas work well in terms of providing accurate type I errors. The Canadian Journal of Statistics 39: 389–404; 2011 © 2011 Statistical Society of Canada

Keywords

Computing methodologies and applications, chi-square limiting distribution, Asymptotic properties of parametric tests, Asymptotic distribution theory in statistics, computer experiment, Computational problems in statistics, order, EM-test

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
13
Top 10%
Top 10%
Average
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