Allowing for the effect of data binning in a Bayesian Normal mixture model

The usual Gibbs sampling framework of the Bayesian mixture model is extended to account for binned data. This model involves the addition of a latent variable in the model which represents simulated values from the believed true distribution at each iteration of the algorithm. The technique results in better model fit and recognition of the more subtle aspects of the density of the data.

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Year of publication:	2010
Authors:	Alston, C.L. ; Mengersen, K.L.
Published in:	Computational Statistics & Data Analysis. - Elsevier, ISSN 0167-9473. - Vol. 54.2010, 4, p. 916-923
Publisher:	Elsevier

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Type of publication:	Article
Source:	RePEc - Research Papers in Economics

Persistent link: https://www.econbiz.de/10008550861