Functions to perform Approximate Bayesian Computation (ABC) using simulated data

Documentation for package ‘abc’ version 1.0

abc	Parameter estimation via Approximate Bayesian Computation (ABC)
abc.return	Parameter estimation via Approximate Bayesian Computation (ABC)
cv4abc	Cross validation for Approximate Bayesian Computation (ABC)
getmode	Summaries of posterior samples generated by ABC algortithms
hist.abc	Posterior histograms
models	A set of R objects used to illustrate model selection in an ABC framework
par.sim	A set of objects used to estimate the population mean and variance in a Gaussian model with ABC.
plot.abc	Diagnostic plots for ABC
plot.cv4abc	Cross-validation plots for ABC
post.mu	A set of objects used to estimate the population mean and variance in a Gaussian model with ABC.
post.sigma2	A set of objects used to estimate the population mean and variance in a Gaussian model with ABC.
postpr	Estimating posterior model probabilities
stat.obs	A set of objects used to estimate the population mean and variance in a Gaussian model with ABC.
stat.sim	A set of objects used to estimate the population mean and variance in a Gaussian model with ABC.
summary.abc	Summaries of posterior samples generated by ABC algortithms
summary.cv4abc	Calculates the cross-validation prediction error
summary.postpr	Posterior model probabilities and Bayes factors
tajima.obs	A set of R objects used to illustrate model selection in an ABC framework
tajima.sim	A set of R objects used to illustrate model selection in an ABC framework