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Normal Mixture Model with General Linear Regressive Restriction: Applied to Microarray Gene Clustering
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 Title & Authors
Normal Mixture Model with General Linear Regressive Restriction: Applied to Microarray Gene Clustering
Kim, Seung-Gu;
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 Abstract
In this paper, the normal mixture model subjected to general linear restriction for component-means based on linear regression is proposed, and its fitting method by EM algorithm and Lagrange multiplier is provided. This model is applied to gene clustering of microarray expression data, which demonstrates it has very good performances for real data set. This model also allows to obtain the clusters that an analyst wants to find out in the fashion that the hypothesis for component-means is represented by the design matrices and the linear restriction matrices.
 Keywords
Normal mixture model;general linear restriction;EM algorithm;microarray;gene clustering;
 Language
Korean
 Cited by
1.
합성된 평균과 분산을 가진 군집 식별,김승구;

Communications for Statistical Applications and Methods, 2011. vol.18. 3, pp.391-401 crossref(new window)
1.
Identification of Cluster with Composite Mean and Variance, Communications for Statistical Applications and Methods, 2011, 18, 3, 391  crossref(new windwow)
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