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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
128 Current Trends in Bayesian Methodology with Applications
developed for o nline infer e nce of static parameters (online Bayesian sequential
Monte Carlo or BSMC) by [14]). A dynamic linear model with Gaussian errors
is chosen since it is the easiest form of state space model, and would be a
good starting point to test our method. Average p e rformance is measured
across many replications of simulated data. To keep the computation-time
comparison fair, all methods were implemented in R [19]. T
INLA
is usually set
at so me value up till which INLA produces results extremely quickly. For
this example, it was fo und to be around 20, hence T
INLA
= 20.
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Publisher Resources

ISBN: 9781482235128