profdpm: Profile Inference for Dirichlet Process Mixtures and Other...
In profdpm: Profile Dirichlet Process Mixtures
Description
This package facilitates profile inference (inference at the posterior mode) for a class of product partition models (PPM). The Dirichlet process mixture is a specific case in this class and is selected by default. These methods search for the maximum posterior (MAP) estimate for the cluster partition in the PPM.
Details
Package: profdpm
Type: Package
Version: 2.0
Date: 2010-04-15
License: GPL (>=2)
LazyLoad: yes
Contents
profLinear Linear Product Partition Models
profBinary Binary Product Partition Models
pci Partition Comparison Indices
Author(s)
Matt Shotwell
Maintainer: Matt Shotwell <shotwelm@musc.edu>
profdpm documentation built on May 2, 2019, 4:56 p.m.
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
Description
This package facilitates profile inference (inference at the posterior mode) for a class of product partition models (PPM). The Dirichlet process mixture is a specific case in this class and is selected by default. These methods search for the maximum posterior (MAP) estimate for the cluster partition in the PPM.
Details
| Package: | profdpm |
| Type: | Package |
| Version: | 2.0 |
| Date: | 2010-04-15 |
| License: | GPL (>=2) |
| LazyLoad: | yes |
Contents
profLinearLinear Product Partition ModelsprofBinaryBinary Product Partition ModelspciPartition Comparison Indices
Author(s)
Matt Shotwell Maintainer: Matt Shotwell <shotwelm@musc.edu>
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
Embedding an R snippet on your website
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.