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 non-empty 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 <firstname.lastname@example.org>, Kung-Sik Chan <email@example.com>|
|Date of publication||2012-10-29 13:13:36|
|Maintainer||Kwang Woo Ahn <firstname.lastname@example.org>|
|License||GPL (>= 2)|
BGSIMD-package: 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
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.