Estimate gaussian (mixture) density from a set of weighted samples

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Published on 2010-03-22T13:48:02Z Indexed on 2010/03/22 13:51 UTC
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Assume I have a set of weighted samples, where each samples has a corresponding weight between 0 and 1. I'd like to estimate the parameters of a gaussian mixture distribution that is biased towards the samples with higher weight. In the usual non-weighted case gaussian mixture estimation is done via the EM algorithm. Does anyone know an implementation (any language is ok) that permits passing weights? If not, does anyone know how to modify the algorithm to account for the weights? If not, can some one give me a hint on how to incorporate the weights in the initial formula of the maximum-log-likelihood formulation of the problem?

Thanks!

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