Classification with a Mixture Model Having an Increasing Number of Components View Full Text


Ontology type: schema:Chapter     


Chapter Info

DATE

2009-07-31

AUTHORS

Odile Pons

ABSTRACT

This paper concerned is with estimation of the components and classification in semi-parametric mixture models with increasing number of components as the sample size grows. Properties of the penalized maximum likelihood estimators are presented: consistency, rates of convergence and asymptotic normality, under additional assumptions. A random classification of the observations is based on the same criterium and some consistency properties are established. More... »

PAGES

261-269

Book

TITLE

Advances in Data Analysis, Data Handling and Business Intelligence

ISBN

978-3-642-01043-9
978-3-642-01044-6

Identifiers

URI

http://scigraph.springernature.com/pub.10.1007/978-3-642-01044-6_24

DOI

http://dx.doi.org/10.1007/978-3-642-01044-6_24

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1016431652


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