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).

Install the latest version of this package by entering the following in R:
source("https://bioconductor.org/biocLite.R")
biocLite("iterativeBMA")
AuthorKa Yee Yeung, University of Washington, Seattle, WA, with contributions from Adrian Raftery and Ian Painter
Bioconductor views Classification Microarray
Date of publicationNone
MaintainerKa Yee Yeung <kayee@u.washington.edu>
LicenseGPL (>= 2)
Version1.34.0
http://faculty.washington.edu/kayee/research.html

View on Bioconductor

Functions

bma.predict Man page
bma.punct.string Man page
brier.score Man page
BssWssFast Man page
convertModelName Man page
convertSingleName Man page
imageplot.bma.mod Man page
imageplot.iterate.bma Man page
iterateBMAglm Man page
iterateBMAglm.train Man page
iterateBMAglm.train.predict Man page
iterateBMAglm.train.predict.test Man page
iterateBMAglm.wrapper Man page
iterateBMAinit Man page
iterativeBMA Man page
iterativeBMA-internal Man page
iterativeBMA-package Man page
maxExpValueKY Man page
minExpValueKY Man page
testClass Man page
testData Man page
trainClass Man page
trainData Man page
zero.threshold Man page

Questions? Problems? Suggestions? or email at ian@mutexlabs.com.

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