Approximate Bayesian Computation via Random Forests
Create an ABC-RF object: a classification random forest from a referen...
Predict posterior covariance between two parameters for new data using...
Plot the posterior density given a new summary statistic
Calculate and plot for different numbers of tree, the out-of-bag error...
Calculate and plot for different numbers of tree, the out-of-bag mean ...
Plot of an ABC-RF object
Plot of a reg-ABC-RF object
Predict and evaluate the posterior probability of the MAP for new data...
Predict posterior expectation, median, variance and quantiles given a ...
Predict out-of-bag posterior expectation, median, variance, quantiles ...
Read a reference table simulated from DIYABC
Create a reg-ABC-RF object: a regression random forest from a referenc...
Variable importance plot from a random forest
Performs Approximate Bayesian Computation (ABC) model choice and parameter inference via random forests. Pudlo P., Marin J.-M., Estoup A., Cornuet J.-M., Gautier M. and Robert C. P. (2016) <doi:10.1093/bioinformatics/btv684>. Estoup A., Raynal L., Verdu P. and Marin J.-M. <http://journal-sfds.fr/article/view/709>. Raynal L., Marin J.-M., Pudlo P., Ribatet M., Robert C. P. and Estoup A. (2019) <doi:10.1093/bioinformatics/bty867>.