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reglogit (version 1.2-2)

Simulation-based Regularized Logistic Regression

Description

Regularized (polychotomous) logistic regression by Gibbs sampling. The package implements subtly different MCMC schemes with varying efficiency depending on the data type (binary v. binomial, say) and the desired estimator (regularized maximum likelihood, or Bayesian maximum a posteriori/posterior mean, etc.) through a unified interface.

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Version

Install

install.packages('reglogit')

Monthly Downloads

293

Version

1.2-2

License

LGPL

Maintainer

Robert Gramacy

Last Published

January 15th, 2014

Functions in reglogit (1.2-2)

pima

Pima Indian Data
reglogit-package

Simulation-based Regularized Logistic Regression
reglogit

Gibbs sampling for regularized logistic regression
reglogit-internal

Internal reglogit Functions
predict.reglogit

Prediction for regularized (polychotomous) logistic regression models