Package: abc 2.2.2
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.
Authors:
abc_2.2.2.tar.gz
abc_2.2.2.zip(r-4.5)abc_2.2.2.zip(r-4.4)abc_2.2.2.zip(r-4.3)
abc_2.2.2.tgz(r-4.5-any)abc_2.2.2.tgz(r-4.4-any)abc_2.2.2.tgz(r-4.3-any)
abc_2.2.2.tar.gz(r-4.5-noble)abc_2.2.2.tar.gz(r-4.4-noble)
abc_2.2.2.tgz(r-4.4-emscripten)abc_2.2.2.tgz(r-4.3-emscripten)
abc.pdf |abc.html✨
abc/json (API)
| # Install 'abc' in R: |
| install.packages('abc', repos = c('https://mblumuga.r-universe.dev', 'https://cloud.r-project.org')) |
This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.
Last updated 3 months agofrom:b9cbc1be3a. Checks:8 OK. Indexed: yes.
| Target | Result | Latest binary |
|---|---|---|
| Doc / Vignettes | OK | Feb 01 2025 |
| R-4.5-win | OK | Feb 01 2025 |
| R-4.5-mac | OK | Feb 01 2025 |
| R-4.5-linux | OK | Feb 01 2025 |
| R-4.4-win | OK | Feb 01 2025 |
| R-4.4-mac | OK | Feb 01 2025 |
| R-4.3-win | OK | Feb 01 2025 |
| R-4.3-mac | OK | Feb 01 2025 |
Exports:abccv4abccv4postprexpected.deviancegfitgfitpcapostpr
Dependencies:abc.datalatticelocfitMASSMatrixMatrixModelsnnetquantregSparseMsurvival
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| Parameter estimation with Approximate Bayesian Computation (ABC) | abc abc.return |
| Cross validation for Approximate Bayesian Computation (ABC) | cv4abc |
| Leave-one-our cross validation for model selection ABC | cv4postpr |
| Expected deviance | expected.deviance |
| Goodness of fit | gfit |
| Goodness of fit with principal component analysis | gfitpca |
| Posterior histograms | hist.abc |
| Diagnostic plots for ABC | plot.abc |
| Cross-validation plots for ABC | plot.cv4abc |
| Barplot of model misclassification | plot.cv4postpr |
| Goodness-of-fit plot for ABC | plot.gfit |
| Estimating posterior model probabilities | postpr |
| Summaries of posterior samples generated by ABC algortithms | getmode summary.abc |
| Calculates the cross-validation prediction error | summary.cv4abc |
| Confusion matrix and misclassification probabilities of models | summary.cv4postpr |
| Calculates the p-value of the goodness-of-fit test. | summary.gfit |
| Posterior model probabilities and Bayes factors | summary.postpr |
