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abc (version 1.7)

Tools for Approximate Bayesian Computation (ABC)

Description

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

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Version

Install

install.packages('abc')

Monthly Downloads

1,391

Version

1.7

License

GPL (>= 3)

Maintainer

Blum Michael

Last Published

June 6th, 2013

Functions in abc (1.7)

plot.cv4abc

Cross-validation plots for ABC

cv4abc

Cross validation for Approximate Bayesian Computation (ABC)

summary.postpr

Posterior model probabilities and Bayes factors

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).

musigma2

A set of objects used to estimate the population mean and variance in a Gaussian model with ABC.

summary.cv4abc

Calculates the cross-validation prediction error

summary.cv4postpr

Confusion matrix and misclassification probabilities of models

abc

Parameter estimation with Approximate Bayesian Computation (ABC)

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).

plot.abc

Diagnostic plots for ABC