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Estimating the mixing proportion in a semiparametric mixture model

Authors
Song, SeongjooNicolae, Dan L.Song, Jongwoo
Issue Date
1-Oct-2010
Publisher
ELSEVIER
Keywords
Clustering; Semiparametric mixture model
Citation
COMPUTATIONAL STATISTICS & DATA ANALYSIS, v.54, no.10, pp.2276 - 2283
Indexed
SCIE
SCOPUS
Journal Title
COMPUTATIONAL STATISTICS & DATA ANALYSIS
Volume
54
Number
10
Start Page
2276
End Page
2283
URI
https://scholar.korea.ac.kr/handle/2021.sw.korea/115535
DOI
10.1016/j.csda.2010.04.007
ISSN
0167-9473
Abstract
In this paper, we investigate methods of estimating the mixing proportion in the case when one of the probability densities is not specified analytically in a mixture model. The methodology we propose is motivated by a sequential clustering algorithm. After a sequential clustering algorithm finds the center of a cluster, the next step is to identify observations belonging to that cluster. If we assume that the center of the cluster is known and that the distribution of observations not belonging to the cluster is unknown, the problem of identifying observations in the cluster is similar to the problem of estimating the mixing proportion in a special two-component mixture model. The mixing proportion can be considered as the proportion of observations belonging to the cluster. We propose two estimators for parameters in the model and compare the performance of these two estimators in several different cases. (C) 2010 Elsevier B.V. All rights reserved.
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