Package: iterativeBMAsurv 1.71.0

Ka Yee Yeung

iterativeBMAsurv: The Iterative Bayesian Model Averaging (BMA) Algorithm For Survival Analysis

The iterative Bayesian Model Averaging (BMA) algorithm for survival analysis is a variable selection method for applying survival analysis to microarray data.

Authors:Amalia Annest, University of Washington, Tacoma, WA Ka Yee Yeung, University of Washington, Seattle, WA

iterativeBMAsurv_1.71.0.tar.gz
iterativeBMAsurv_1.71.0.zip(r-4.7)iterativeBMAsurv_1.71.0.zip(r-4.6)iterativeBMAsurv_1.71.0.zip(r-4.5)
iterativeBMAsurv_1.71.0.tgz(r-4.6-any)iterativeBMAsurv_1.71.0.tgz(r-4.5-any)
iterativeBMAsurv_1.71.0.tar.gz(r-4.7-any)iterativeBMAsurv_1.71.0.tar.gz(r-4.6-any)
iterativeBMAsurv_1.71.0.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION
card.svg |card.png
iterativeBMAsurv/json (API)

# Install 'iterativeBMAsurv' in R:

install.packages('iterativeBMAsurv', repos = c('https://bioc.r-universe.dev', 'https://cloud.r-project.org'))

Datasets:

testCens - Sample Test Data for the Iterative BMA Algorithm for Survival Analysis
testData - Sample Test Data for the Iterative BMA Algorithm for Survival Analysis
testSurv - Sample Test Data for the Iterative BMA Algorithm for Survival Analysis
trainCens - Sample Training Data for the Iterative BMA Algorithm for Survival Analysis
trainData - Sample Training Data for the Iterative BMA Algorithm for Survival Analysis
trainSurv - Sample Training Data for the Iterative BMA Algorithm for Survival Analysis

On BioConductor:iterativeBMAsurv-1.71.0(bioc 3.24)iterativeBMAsurv-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.

microarray

3.30 score 8 scripts 372 downloads 1 mentions 17 exports 11 dependencies

Last updated from:e0e1d61d55. Checks:1 ERROR, 7 WARNING, 2 OK. Indexed: yes.

Target	Result	Time
bioc-checks	ERROR	131
linux-devel-x86_64	WARNING	182
source / vignettes	OK	164
linux-release-x86_64	WARNING	167
macos-release-arm64	WARNING	95
macos-oldrel-arm64	WARNING	119
windows-devel	WARNING	82
windows-release	WARNING	145
windows-oldrel	WARNING	101
wasm-release	OK	96

Exports:assignRiskGroup crossVal crossVal.final.calc crossVal.fold crossVal.init crossVal.run crossVal.tabulate imageplot.bma.mod imageplot.iterate.bma.surv iterateBMAinit iterateBMAsurv.train iterateBMAsurv.train.predict.assess iterateBMAsurv.train.wrapper predictBicSurv predictiveAssessCategory printTopGenes singleGeneCoxph

Dependencies:BMA DEoptimR inline lattice leaps Matrix mvtnorm pcaPP robustbase rrcov survival

The Iterative Bayesian Model Averaging Algorithm For Survival Analysis

Rendered fromiterativeBMAsurv.Rnwusingutils::Sweave

Last update: 2013-11-01
Started: 2013-11-01

Citation

Development and contributors

Readme and manuals

Help Manual

Help page	Topics
The Iterative Bayesian Model Averaging (BMA) algorithm for survival analysis	iterativeBMAsurv-package iterativeBMAsurv
Cross Validation for Iterative Bayesian Model Averaging	crossVal
An image plot visualization tool	imageplot.iterate.bma.surv
Iterative Bayesian Model Averaging: training	iterateBMAsurv.train
Iterative Bayesian Model Averaging: training, prediction, assessment	iterateBMAsurv.train.predict.assess
Iterative Bayesian Model Averaging: training	iterateBMAsurv.train.wrapper
Predicted patient risk scores from iterative Bayesian Model Averaging	predictBicSurv
Risk Groups: assignment of patient test samples	predictiveAssessCategory
Write a training set including the top-ranked G variables from a sorted matrix to file	printTopGenes
Univariate Cox Proportional Hazards Model for selecting top log-ranked predicitve variables	singleGeneCoxph
Sample Test Data for the Iterative BMA Algorithm for Survival Analysis	testCens
Sample Test Data for the Iterative BMA Algorithm for Survival Analysis	testData
Sample Test Data for the Iterative BMA Algorithm for Survival Analysis	testSurv
Sample Training Data for the Iterative BMA Algorithm for Survival Analysis	trainCens
Sample Training Data for the Iterative BMA Algorithm for Survival Analysis	trainData
Sample Training Data for the Iterative BMA Algorithm for Survival Analysis	trainSurv