Consistency of the MLE under Mixture Models.
In: Statistical Science, Jg. 32 (2017-02-01), Heft 1, S. 47-63
Online
academicJournal
Zugriff:
The large-sample properties of likelihood-based statistical inference under mixture models have received much attention from statisticians. Although the consistency of the nonparametric MLE is regarded as a standard conclusion, many researchers ignore the precise conditions required on the mixture model. An incorrect claim of consistency can lead to false conclusions even if the mixture model under investigation seems well behaved. Under a finite normal mixture model, for instance, the consistency of the plain MLE is often erroneously assumed in spite of recent research breakthroughs. This paper streamlines the consistency results for the nonparametric MLE in general, and in particular for the penalized MLE under finite normal mixture models. [ABSTRACT FROM AUTHOR]
Copyright of Statistical Science is the property of Institute of Mathematical Statistics and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
Titel: |
Consistency of the MLE under Mixture Models.
|
---|---|
Autor/in / Beteiligte Person: | Chen, Jiahua |
Link: | |
Zeitschrift: | Statistical Science, Jg. 32 (2017-02-01), Heft 1, S. 47-63 |
Veröffentlichung: | 2017 |
Medientyp: | academicJournal |
ISSN: | 0883-4237 (print) |
DOI: | 10.1214/16-STS578 |
Sonstiges: |
|