Provides a variety of methods from Rao (2003, ISBN:0-471-41374-7) and some other research articles to deal with several specific small area area- level models in Bayesian framework. Models provided range from the basic Fay-Herriot model to its improvement such as You-Chapman models, unmatched models, spatial models and so on. Different types of priors for specific parameters could be chosen to obtain MCMC posterior draws. The main sampling function is written in C with GSL lab so as to facilitate the computation. Model internal checking and model comparison criteria are also involved.
Changes in Version 1.0-1
o Documentation update. o Change in the specification of the model. Model is directly specified via function BayesSAE o BayesSAE returns with a S3 class of object and generics are involved. o Posterior draws are allowed to coerce to the mcmc class, which can are allowed to use function in the coda package for further diagnosis
Changes in Version 1.0-2
o Update of Maintainer's email address o Registration of the S3 methods