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Nonparametric inference in multivariate mixtures

Hall, Peter; Neeman, Amnon; Elmore, Ryan; Pakyari, Reza

Description

We consider mixture models in which the components of data vectors from any given subpopulation are statistically independent, or independent in blocks. We argue that if, under this condition of independence, we take a nonparametric view of the problem and allow the number of subpopulations to be quite general, the distributions and mixing proportions can often be estimated root-n consistently. Indeed, we show that, if the data are k-variate and there are p subpopulations, then for each p ≥ 2...[Show more]

CollectionsANU Research Publications
Date published: 2005
Type: Journal article
URI: http://hdl.handle.net/1885/79767
Source: Biometrika
DOI: 10.1093/biomet/92.3.667

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