Tools for Approximate Bayesian Computation (ABC)


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Documentation for package ‘abc’ version 1.8

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abc Parameter estimation with Approximate Bayesian Computation (ABC)
abc.return Parameter estimation with Approximate Bayesian Computation (ABC)
cv4abc Cross validation for Approximate Bayesian Computation (ABC)
cv4postpr Leave-one-our cross validation for model selection ABC
expected.deviance Expected deviance
getmode Summaries of posterior samples generated by ABC algortithms
hist.abc Posterior histograms
human A set of R objects containing observed data from three human populations, and simulated data under three different demographic models. The data set is used to illustrate model selection and parameter inference in an ABC framework (see the package's vignette for more details).
models A set of R objects containing observed data from three human populations, and simulated data under three different demographic models. The data set is used to illustrate model selection and parameter inference in an ABC framework (see the package's vignette for more details).
musigma2 A set of objects used to estimate the population mean and variance in a Gaussian model with ABC.
par.italy.sim A set of R objects containing observed data from three human populations, and simulated data under three different demographic models. The data set is used to illustrate model selection and parameter inference in an ABC framework (see the package's vignette for more details).
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
plot.cv4postpr Barplot of model misclassification
post.bott Data to illustrate the posterior predictive checks for the data 'human'. 'ppc' and 'human' are used to illustrate model selection and parameter inference in an ABC framework (see the package's vignette for more details).
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
ppc Data to illustrate the posterior predictive checks for the data 'human'. 'ppc' and 'human' are used to illustrate model selection and parameter inference in an ABC framework (see the package's vignette for more details).
stat.3pops.sim A set of R objects containing observed data from three human populations, and simulated data under three different demographic models. The data set is used to illustrate model selection and parameter inference in an ABC framework (see the package's vignette for more details).
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.
stat.voight A set of R objects containing observed data from three human populations, and simulated data under three different demographic models. The data set is used to illustrate model selection and parameter inference in an ABC framework (see the package's vignette for more details).
summary.abc Summaries of posterior samples generated by ABC algortithms
summary.cv4abc Calculates the cross-validation prediction error
summary.cv4postpr Confusion matrix and misclassification probabilities of models
summary.postpr Posterior model probabilities and Bayes factors