Approximate Bayesian Computation via Random Forests

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Documentation for package ‘abcrf’ version 1.9

• DESCRIPTION file.

Help Pages

abcrf	Create an ABC-RF object: a classification random forest from a reference table towards performing an ABC model choice
abcrf.formula	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
covRegAbcrf.regAbcrf	Predict posterior covariance between two parameters for new data using two reg-ABC-RF objects
densityPlot	Plot the posterior density given a new summary statistic
densityPlot.regAbcrf	Plot the posterior density given a new summary statistic
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
plot.abcrf	Plot of an ABC-RF object
plot.regAbcrf	Plot of a reg-ABC-RF object
predict.abcrf	Predict and evaluate the posterior probability of the MAP for new data using an ABC-RF object
predict.regAbcrf	Predict posterior expectation, median, variance and quantiles given a new dataset using a reg-ABC-RF object
predictOOB	Predict out-of-bag posterior expectation, median, variance, quantiles and error measures using a reg-ABC-RF object
predictOOB.regAbcrf	Predict out-of-bag posterior expectation, median, variance, quantiles and error measures using a reg-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
regAbcrf.formula	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
snp	A simulated example in population genetics
snp.obs	A simulated example in population genetics
variableImpPlot	Variable importance plot from a random forest