Package: iterativeBMA 1.71.0

Ka Yee Yeung
iterativeBMA: The Iterative Bayesian Model Averaging (BMA) algorithm
The iterative Bayesian Model Averaging (BMA) algorithm is a variable selection and classification algorithm with an application of classifying 2-class microarray samples, as described in Yeung, Bumgarner and Raftery (Bioinformatics 2005, 21: 2394-2402).
Authors:
iterativeBMA_1.71.0.tar.gz
iterativeBMA_1.71.0.zip(r-4.7)iterativeBMA_1.71.0.zip(r-4.6)iterativeBMA_1.71.0.zip(r-4.5)
iterativeBMA_1.71.0.tgz(r-4.6-any)iterativeBMA_1.71.0.tgz(r-4.5-any)
iterativeBMA_1.71.0.tar.gz(r-4.7-any)iterativeBMA_1.71.0.tar.gz(r-4.6-any)
iterativeBMA_1.71.0.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
card.svg |card.png
iterativeBMA/json (API)
| # Install 'iterativeBMA' in R: |
| install.packages('iterativeBMA', repos = c('https://bioc.r-universe.dev', 'https://cloud.r-project.org')) |
- testClass - Sample Test Data for the Iterative BMA Algorithm
- testData - Sample Test Data for the Iterative BMA Algorithm
- trainClass - Sample Training Data for the Iterative BMA Algorithm
- trainData - Sample Training Data for the Iterative BMA Algorithm
On BioConductor:iterativeBMA-1.71.0(bioc 3.24)iterativeBMA-1.70.0(bioc 3.23)
This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.
Last updated from:c138cdaea0. Checks:1 ERROR, 7 NOTE, 2 OK. Indexed: yes.
| Target | Result | Time | Files | Syslog |
|---|---|---|---|---|
| bioc-checks | ERROR | 122 | ||
| linux-devel-x86_64 | NOTE | 148 | ||
| source / vignettes | OK | 239 | ||
| linux-release-x86_64 | NOTE | 149 | ||
| macos-release-arm64 | NOTE | 112 | ||
| macos-oldrel-arm64 | NOTE | 76 | ||
| windows-devel | NOTE | 90 | ||
| windows-release | NOTE | 81 | ||
| windows-oldrel | NOTE | 105 | ||
| wasm-release | OK | 86 |
Exports:bma.predictbrier.scoreBssWssFastimageplot.iterate.bmaiterateBMAglm.trainiterateBMAglm.train.predictiterateBMAglm.train.predict.testiterateBMAglm.wrapper
Dependencies:BiobaseBiocGenericsBMADEoptimRgenericsinlinelatticeleapsMatrixmvtnormpcaPProbustbaserrcovsurvival
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| The Iterative Bayesian Model Averaging (BMA) algorithm | iterativeBMA-package iterativeBMA |
| Predicted Probabilities from Bayesian Model Averaging | bma.predict |
| Brier Score: assessment of prediction accuracy | brier.score |
| Between-groups sum-of-squares to within-groups sum-of-squares ratio | BssWssFast |
| An image plot visualization tool | imageplot.iterate.bma |
| Iterative Bayesian Model Averaging: training step | iterateBMAglm.train |
| Iterative Bayesian Model Averaging: training and prediction | iterateBMAglm.train.predict |
| Iterative Bayesian Model Averaging: training, prediction and testing | iterateBMAglm.train.predict.test |
| Iterative Bayesian Model Averaging | iterateBMAglm.wrapper |
| Sample Test Data for the Iterative BMA Algorithm | testClass |
| Sample Test Data for the Iterative BMA Algorithm | testData |
| Sample Training Data for the Iterative BMA Algorithm | trainClass |
| Sample Training Data for the Iterative BMA Algorithm | trainData |