CRAN/E | sahpm

sahpm

Variable Selection using Simulated Annealing

Installation

About

Highest posterior model is widely accepted 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.

Key Metrics

Version 1.0.1
R ≥ 3.4
Published 2022-02-24 960 days ago
Needs compilation? no
License GPL-2
CRAN checks sahpm results

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Maintainer

Maintainer

Arnab Maity

Authors

Arnab Maity

aut / cre

Sanjib Basu

ctb

Material

README
Reference manual
Package source

macOS

r-release

arm64

r-oldrel

arm64

r-release

x86_64

r-oldrel

x86_64

Windows

r-devel

x86_64

r-release

x86_64

r-oldrel

x86_64

Depends

R ≥ 3.4

Imports

stats
mvtnorm
utils