View : 16 Download: 0

Estimating the mixing proportion in a semiparametric mixture model

Title
Estimating the mixing proportion in a semiparametric mixture model
Authors
Song S.Nicolae D.L.Song J.
Ewha Authors
송종우
SCOPUS Author ID
송종우scopus
Issue Date
2010
Journal Title
Computational Statistics and Data Analysis
ISSN
0167-9473JCR Link
Citation
vol. 54, no. 10, pp. 2276 - 2283
Indexed
SCIE; SCOPUS WOS scopus
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. © 2010 Elsevier B.V. All rights reserved.
DOI
10.1016/j.csda.2010.04.007
Appears in Collections:
자연과학대학 > 통계학전공 > Journal papers
Files in This Item:
There are no files associated with this item.
Export
RIS (EndNote)
XLS (Excel)
XML


qrcode

Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.

BROWSE