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Thamerus, Markus (1996): Fitting a Finite Mixture Distribution to a Variable Subject to Heteroscedastic Measurement Error. Collaborative Research Center 386, Discussion Paper 48 [PDF, 300kB]


We consider the case where a latent variable X cannot be observed directly and instead a variable W=X+U with an heteroscedastic measurement error U is observed. It is assumed that the distribution of the true variable X is a mixture of normals and a type of the EM algorithm is applied to find approximate ML estimates of the distribution parameters of X.

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