print.cv.logit.reg {CDLasso} | R Documentation |
Print short summary of results of cross validation for Greedy Coordinate Descent for Logistric Regression.
## S3 method for class 'cv.logit.reg' print(x, ...)
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Output of cv.logit.reg. Must be of class "cv.logit.reg" |
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print.cv.logit.reg
produces output from cv.logit.reg
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Edward Grant, Kenneth Lange, Tong Tong Wu
Maintainer: Edward Grant edward.m.grant@gmail.com
Wu, T.T., Chen, Y.F., Hastie, T., Sobel E. and Lange, K. (2009). Genome-wide association analysis by lasso penalized logistic regression. Bioinformatics, Volume 25, No 6, 714-721.
set.seed(101) n=250;p=50 beta=c(1,1,1,1,1,rep(0,p-5)) x=matrix(rnorm(n*p),p,n) xb = t(x) %*% beta logity=exp(xb)/(1+exp(xb)) y=rbinom(n=length(logity),prob=logity,size=1) rownames(x)<-1:nrow(x) colnames(x)<-1:ncol(x) lam.vec = (0:15)*2 #K-fold cross validation cv <- cv.logit.reg(x,y,5,lam.vec) plot(cv) #Lasso penalized logistic regression using optimal lambda out<-logit.reg(x,y,cv$lam.opt) #Re-estimate parameters without penalization out2<-logit.reg(x[out$selected,],y,0) out2$estimate