Nonparametric estimation of component distributions in a multivariate mixture
Suppose k-variate data are drawn from a mixture of two distributions, each having independent components. It is desired to estimate the univariate marginal distributions in each of the products, as well as the mixing proportion. This is the setting of two-class, fully parametrized latent models that has been proposed for estimating the distributions of medical test results when disease status is unavailable. The problem is one of inference in a mixture of distributions without training data,...[Show more]
|Collections||ANU Research Publications|
|Source:||The Annals of Statistics|
|01_Hall_Nonparametric_Estimation_2003.pdf||297.55 kB||Adobe PDF|
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