# Approximate Bayesian Computation via Random Forests

## 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