Description Usage Arguments Value References See Also Examples
View source: R/iBMAcontrolLM.R
Assigns default control parameters for iterateBMAlm
, and
allows setting control parameter values.
1 2  iBMAcontrolLM( OR = 20, nbest = 10, maxNvar = 30, thresProbne0 = 1,
keepModels = FALSE, maxIter = 200000)

OR 
A number specifying the maximum ratio for excluding models in Occam's window. 
nbest 
A positive integer specifying the number of models of each size to be considered by leapsandbounds in determining the model space for Bayesian Model Averaging. The default value is 10. 
maxNvar 
A positive integer specifying the maximum number of variables (excluding the intercept) used in each iteration of BMA. The default value is 30. 
thresProbne0 
Threshold (in percent) for the posterior probability that
each variable is has a nonzero coefficient (in percent).
Variables with posterior probability less than 
keepModels 
A logical value indicating whether or not to keep the BMA models
from all of the iterations and apply Occam's window using 
maxIter 
A positive integer giving a limit on the number of iterations of

A list of values for the named control parameters to be passed
to a version of the function bicreg
from the BMA
package that has been modified to handle prior probabilities.
K. Lo, A. E. Raftery, K. M. Dombek, J. Zhu, E. E. Schadt, R. E. Bumgarner and K. Y. Yeung (2012), Integrating External Biological Knowledge in the Construction of Regulatory Networks from Timeseries Expression Data, BMC Systems Biology, 6:101.
K. Y. Yeung, K. M. Dombek, K. Lo, J. E. Mittler, J. Zhu, E. E. Schadt, R. E. Bumgarner and A. E. Raftery (2011), Construction of regulatory networks using expression timeseries data of a genotyped population, Proceedings of the National Academy of Sciences, 108(48):1943641.
K. Y. Yeung (with contributions from A. E. Raftery and I. Painter), iterativeBMA: The Iterative Bayesian Model Averaging (BMA) algorithm, Bioconductor R package, version 1.8.0 posted in 2009.
K. Y. Yeung, R. E. Bumgarner and A. E. Raftery (2005). Bayesian Model Averaging: Development of an improved multiclass, gene selection and classification tool for microarray data. Bioinformatics 21:23942402.
A. E. Raftery, J. A. Hoeting, C. T. Volinsky, I. Painter and K. Y. Yeung (2005), BMA: Bayesian Model Averaging, Comnprehensive R Archhive Network (CRAN), package version 3.15.1 posted in 2012.
J. A. Hoeting, D. Madigan, A. E. Raftery, and C. T. Volinsky (1999). Bayesian Model Averaging: a tutorial, Statistical Science 14(4): 382417.
iterateBMAlm
,
networkBMA
do.call
1 2 3 4 5 6 7 8 9  data(dream4)
network < 1
nTimePoints < length(unique(dream4ts10[[network]]$time))
edges1ts10 < networkBMA( data = dream4ts10[[network]][,(1:2)],
nTimePoints = nTimePoints,
control = iBMAcontrolLM(thresProbne0 = 1))

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