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Current Trends in Bayesian Methodology with Applications
book

Current Trends in Bayesian Methodology with Applications

by Satyanshu K. Upadhyay, Umesh Singh, Dipak K. Dey, Appaia Loganathan
May 2015
Intermediate to advanced content levelIntermediate to advanced
680 pages
22h 33m
English
Chapman and Hall/CRC
Content preview from Current Trends in Bayesian Methodology with Applications
482 Current Trends in Bayesian Methodology with Applications
and analyzed with Gaussian RRSM, arguing that estimates ar e still best lin-
ear unbiased predictor (BLUP), and co nditioning on the estimates of V and
ν
2
obtained from EM algorithm. When distributional ass umptions are wrong,
then likelihood based approaches, such as EM algorithm, suffer and do not
provide accurate estimates of model parameters and the predictions become
unreliable. One can use dis tribution free estimation techniques, such as binned
method of moments (MOM) estimation (see [6] and for more robust version
[15]). But binned estimatio n does not provide a ready positive-definite ...
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Publisher Resources

ISBN: 9781482235128