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.

Install the latest version of this package by entering the following in R:

`install.packages("BGSIMD")`

Author | Kwang Woo Ahn <kwooahn@mcw.edu>, Kung-Sik Chan <kung-sik-chan@uiowa.edu> |

Date of publication | 2012-10-29 13:13:36 |

Maintainer | Kwang Woo Ahn <kwooahn@mcw.edu> |

License | GPL (>= 2) |

Version | 1.0 |

**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

NAMESPACE

man

man/rdirichlet.Rd
man/partition.Rd
man/part.Rd
man/block.gibbs.Rd
man/BGSIMD-package.Rd
DESCRIPTION

MD5

R

R/partition.R
R/rdirichlet.R
R/part.R
R/block.gibbs.R
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