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abc

Tools for Approximate Bayesian Computation (ABC)

Implements several ABC algorithms for performing parameter estimation, model selection, and goodness-of-fit. Cross-validation tools are also available for measuring the accuracy of ABC estimates, and to calculate the misclassification probabilities of different models.

Functions (17)

abc

Parameter estimation with Approximate Bayesian Computation (ABC)

Cross validation for Approximate Bayesian Computation (ABC)

Leave-one-our cross validation for model selection ABC

expected.deviance

Expected deviance

gfit

Goodness of fit

Goodness of fit with principal component analysis

Posterior histograms

Diagnostic plots for ABC

plot.cv4abc

Cross-validation plots for ABC

plot.cv4postpr

Barplot of model misclassification

Goodness-of-fit plot for ABC

Estimating posterior model probabilities

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.gfit

Calculates the p-value of the goodness-of-fit test.

summary.postpr

Posterior model probabilities and Bayes factors

abc

Tools for Approximate Bayesian Computation (ABC)

v2.1

GPL (>= 3)

Authors

Csillery Katalin [aut], Lemaire Louisiane [aut], Francois Olivier [aut], Blum Michael [aut, cre]

Initial release

2015-05-04

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