Probability density estimation via an infinite Gaussian mixture model: application to statistical process monitoring

Journal article

Open access

Peer reviewed

T Chen, J Morris and E Martin

J ROY STAT SOC C-APP, Vol.55, pp.699-715

2006

Abstract

Dirichlet process mixtures

infinite Gaussian mixture model

Markov chain Monte Carlo methods

multivariate statistical process monitoring

probability density estimation

PRINCIPAL COMPONENT ANALYSIS

BAYESIAN-ANALYSIS

UNKNOWN NUMBER

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TextSRIDA, Open Access

url

http://dx.doi.org/10.1111/j.1467-9876.2006.00560.xView

Published (Version of record)

Title: Probability density estimation via an infinite Gaussian mixture model: application to statistical process monitoring
Creators: T Chen
J Morris
E Martin
Publication Details: J ROY STAT SOC C-APP, Vol.55, pp.699-715
Publisher: BLACKWELL PUBLISHING
Publication Date: 2006
Identifiers: 99515730602346; WOS:000241390200008
Academic Unit: School of Chemistry and Chemical Engineering
Language: English
Resource Type: Journal article