CRAN/E | LearnBayes

LearnBayes

Functions for Learning Bayesian Inference

Installation

About

A collection of functions helpful in learning the basic tenets of Bayesian statistical inference. It contains functions for summarizing basic one and two parameter posterior distributions and predictive distributions. It contains MCMC algorithms for summarizing posterior distributions defined by the user. It also contains functions for regression models, hierarchical models, Bayesian tests, and illustrations of Gibbs sampling.

Key Metrics

Version 2.15.1
Published 2018-03-18 2232 days ago
Needs compilation? no
License GPL-2
License GPL-3
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Maintainer

Maintainer

Jim Albert

albert@bgsu.edu

Authors

Jim Albert

Material

Reference manual
Package source

In Views

Bayesian
Distributions
Survival
TeachingStatistics

Vignettes

Introduction to Bayes Factors
Learning About a Binomial Proportion
Introduction to Bayes using Discrete Priors
Introduction to Markov Chain Monte Carlo
Introduction to Multilevel Modeling

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

Old Sources

LearnBayes archive

Reverse Depends

bayeslongitudinal
ProbBayes
psbcGroup

Reverse Imports

cancerTiming
evidence
RSSampling
spatialreg

Reverse Suggests

mistat