For model selection using BIC you can have a look at stepAIC() from package MASS and boot.stepAIC() from package bootStepAIC. For instance,
library(bootStepAIC) boot.stepAIC(glmFit1, data, B = 50, k = log(nrow(n))) where `glmFit1' is the object represinting the fitted model, `data' the data.frame containing the variables for the analysis, `B' the number of bootstrap replicates, and `k' is the multiple of the number of degrees of freedom used for the penalty, which when equal to log(n) is the BIC. By default boot.stepAIC() returns as well the results of stepAIC(). I hope it helps. Best, Dimitris ---- Dimitris Rizopoulos Ph.D. Student Biostatistical Centre School of Public Health Catholic University of Leuven Address: Kapucijnenvoer 35, Leuven, Belgium Tel: +32/(0)16/336899 Fax: +32/(0)16/337015 Web: http://med.kuleuven.be/biostat/ http://www.student.kuleuven.be/~m0390867/dimitris.htm ----- Original Message ----- From: "Tirthadeep" <[EMAIL PROTECTED]> To: <[EMAIL PROTECTED]> Sent: Monday, September 17, 2007 7:36 AM Subject: [R] Stepwise logistic model selection using Cp and BIC criteria > > Hi, > > Is there any package for logistic model selection using BIC and > Mallow's Cp > statistic? If not, then kindly suggest me some ways to deal with > these > problems. > > Thanks. > -- > View this message in context: > http://www.nabble.com/Stepwise-logistic-model-selection-using-Cp-and-BIC-criteria-tf4464430.html#a12729613 > Sent from the R help mailing list archive at Nabble.com. > > ______________________________________________ > R-help@r-project.org mailing list > https://stat.ethz.ch/mailman/listinfo/r-help > PLEASE do read the posting guide > http://www.R-project.org/posting-guide.html > and provide commented, minimal, self-contained, reproducible code. > Disclaimer: http://www.kuleuven.be/cwis/email_disclaimer.htm ______________________________________________ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
