Fluctuation of estimates in an EM procedure for categorical data

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Estimates from an EM algorithm are somewhat sensitive to the initial values for the estimates, and this sensitivity is likely to increase when the model becomes larger and more complicated. In this paper, we examined how the estimates fluctuate during an EM procedure for a recursive model of categorical variables. It is found that the fluctuation takes place mostly during the initial stage of the procedure and that it can be reduced by applying a Bayes method of estimation. Both real and simulated data are used for illustration.
Publisher
TAYLOR & FRANCIS LTD
Issue Date
2005-12
Language
English
Article Type
Article
Keywords

LATENT VARIABLE MODELS; RECURSIVE MODELS; ALGORITHM; LIKELIHOOD

Citation

JOURNAL OF STATISTICAL COMPUTATION AND SIMULATION, v.75, no.12, pp.941 - 957

ISSN
0094-9655
DOI
10.1080/00949650412331299175
URI
http://hdl.handle.net/10203/90097
Appears in Collection
MA-Journal Papers(저널논문)
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