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.

Install the latest version of this package by entering the following in R:
AuthorAmalia Annest, University of Washington, Tacoma, WA Ka Yee Yeung, University of Washington, Seattle, WA
Bioconductor views Microarray
Date of publicationNone
MaintainerKa Yee Yeung <>
LicenseGPL (>= 2)

View on Bioconductor


assignRiskGroup Man page
crossVal Man page Man page
crossVal.fold Man page
crossVal.init Man page Man page
crossVal.tabulate Man page
imageplot.bma.mod Man page
imageplot.iterate.bma.surv Man page
iterateBMAinit Man page
iterateBMAsurv.train Man page
iterateBMAsurv.train.predict.assess Man page
iterateBMAsurv.train.wrapper Man page
iterativeBMAsurv Man page
iterativeBMAsurv-internal Man page
iterativeBMAsurv-package Man page
predictBicSurv Man page
predictiveAssessCategory Man page
printTopGenes Man page
singleGeneCoxph Man page
testCens Man page
testData Man page
testSurv Man page
trainCens Man page
trainData Man page
trainSurv Man page

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