Implement an efficient block Gibbs sampler with incomplete data from a multinomial distribution taking values from the k categories 1,2,...,k, where data are assumed to miss at random and each missing datum belongs to one and only one of m distinct nonempty proper subsets A1, A2,..., Am of 1,2,...,k and the k categories are labelled such that only consecutive A's may overlap.
Author  Kwang Woo Ahn <kwooahn@mcw.edu>, KungSik Chan <kungsikchan@uiowa.edu> 
Date of publication  20121029 13:13:36 
Maintainer  Kwang Woo Ahn <kwooahn@mcw.edu> 
License  GPL (>= 2) 
Version  1.0 
Package repository  View on CRAN 
Installation  Install the latest version of this package by entering the following in R:



All man pages Function index File listing
Man pages  

BGSIMDpackage: Efficient Block Gibbs Sampler with Data from an Incomplete...  
block.gibbs: Efficient Block Gibbs Sampling with Incomplete Data from a...  
part: Partition Sets of Two Sets  
partition: The Coarsest Partition of a Finite Sequence of Sets for Which...  
rdirichlet: Random Sampling from the Dirichlet Distribution 
Functions  

BGSIMD  Man page 
BGSIMDpackage  Man page 
block.gibbs  Man page 
part  Man page 
partition  Man page 
rdirichlet  Man page 
Files  

NAMESPACE
 
man
 
man/rdirichlet.Rd  
man/partition.Rd  
man/part.Rd  
man/block.gibbs.Rd  
man/BGSIMDpackage.Rd  
DESCRIPTION
 
MD5
 
R
 
R/partition.R  
R/rdirichlet.R  
R/part.R  
R/block.gibbs.R 
Questions? Problems? Suggestions? Tweet to @rdrrHQ or email at ian@mutexlabs.com.
Please suggest features or report bugs in the GitHub issue tracker.
All documentation is copyright its authors; we didn't write any of that.
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.