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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.

Type Size Name Uploaded Downloads Labels
conda 129.2 kB | win-64/r-bayessae-1.0_2-r361h796a38f_0.tar.bz2  5 years and 5 months ago 0 main
conda 135.3 kB | osx-64/r-bayessae-1.0_2-r36h466af19_0.tar.bz2  5 years and 5 months ago 0 main
conda 120.4 kB | linux-64/r-bayessae-1.0_2-r36h29659fb_0.tar.bz2  5 years and 5 months ago 0 main

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