The estimation of normal mixtures with latent variables

Gideon Magnus and Jan R. Magnus

Communications in Statistics - Theory and Methods, 2019, vol. 48, issue 5, 1255-1269

Abstract: This paper considers the class of normal latent factor mixture models. It presents a method for estimating the posterior distribution of the parameters, derives analytical expressions for both the first and second derivatives of the posterior kernel (the score and Hessian), and provides posterior approximations that can be computed relatively quickly.

Date: 2019
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DOI: 10.1080/03610926.2018.1429625

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