arnabkrmaity/sahpm: Variable Selection using Simulated Anneling
Version 0.0.9

Highest posterior model is widely accepeted as a good model among available models. In terms of variable selection highest posterior model is often the true model. Our stochastic search process SAHPM based on simulated annealing maximization method tries to find the highest posterior model by maximizing the model space with respect to the posterior probabilities of the models. This package currently contains the SAHPM method only for linear models. The codes for GLM will be added in future.

Getting started

Package details

Maintainer
LicenseGPL-2
Version0.0.9
Package repositoryView on GitHub
Installation Install the latest version of this package by entering the following in R:
install.packages("devtools")
library(devtools)
install_github("arnabkrmaity/sahpm")
arnabkrmaity/sahpm documentation built on Sept. 2, 2017, 12:11 a.m.