Approximate Bayesian Computation via Random Forests


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Documentation for package ‘abcrf’ version 1.8.1

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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