# abcfr 0.9-3

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**I**n conjunction with our reliable ABC model choice via random forest paper, about to be resubmitted to *Bioinformatics*, we have contributed an R package called abcrf that produces a most likely model and its posterior probability out of an ABC reference table. In conjunction with the realisation that we could devise an approximation to the (ABC) posterior probability using a secondary random forest. “We” meaning Jean-Michel Marin and Pierre Pudlo, as I only acted as a beta tester!

The package abcrf consists of three functions:

*abcrf*, which constructs a random forest from a reference table and returns an object of class `abc-rf’;*plot.abcrf*, which gives both variable importance plot of a model choice abc-rf object and the projection of the reference table on the LDA axes;*predict.abcrf*, which predict the model for new data and evaluate the posterior probability of the MAP.

An illustration from the manual:

data(snp) data(snp.obs) mc.rf <- abcrf(snp[1:1e3, 1], snp[1:1e3, -1]) predict(mc.rf, snp[1:1e3, -1], snp.obs)

Filed under: R, Statistics, University life Tagged: ABC, ABC model choice, abcrf, bioinformatics, CRAN, R, random forests, reference table, SNPs

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