abcrf version 1.9

R library to perform Approximate Bayesian Computation via Random Forests

To install the abcrf package

you can use the function install_github from the package remotes:

install_github("jmm34/abcrf")

you can download the file abcrf_1.9.tar.gz and use the command:

install.packages("abcrf_1.9.tar.gz", repos = NULL, type = "source")

the package is also available on the CRAN

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Version

Install

install.packages('abcrf')

Monthly Downloads

262

Version

2.0

License

GPL (>= 2)

Maintainer

JeanMichel Marin

Last Published

December 17th, 2025

Functions in abcrf (2.0)

snp

A simulated example in population genetics

variableImpPlot

Variable importance plot from a random forest

abcrf

Create an ABC-RF object: a classification random forest from a reference table towards performing an ABC model choice

covRegAbcrf

Predict posterior covariance between two parameters for new data using two reg-ABC-RF objects

plot.abcrf

Plot of an ABC-RF object

predict.regAbcrf

Predict posterior expectation, median, variance and quantiles given a new dataset using a reg-ABC-RF object

densityPlot

Plot the posterior density given a new summary statistic

plot.regAbcrf

Plot of a reg-ABC-RF object

err.abcrf

Calculate and plot for different numbers of tree, the out-of-bag errors associated with an ABC-RF object

err.regAbcrf

Calculate and plot for different numbers of tree, the out-of-bag mean squared errors associated with a REG-ABC-RF object

predictOOB

Predict out-of-bag posterior expectation, median, variance, quantiles and error measures using a reg-ABC-RF object

predict.abcrf

Predict and evaluate the posterior probability of the MAP for new data using an ABC-RF object

readRefTable

Read a reference table simulated from DIYABC

regAbcrf

Create a reg-ABC-RF object: a regression random forest from a reference table aimed out predicting posterior expectation, variance and quantiles for a parameter