cv.lambda {slr} | R Documentation |
K-fold Cross Validation for Smoothed Logistic Regression
cv.lambda(y,Z,Chrom=NULL,lambda1,lambda2,K=10)
y |
binary response variable |
Z |
matrix of predictor variables; rows correspond to probes and columns correspond to subjects. |
Chrom |
chromsone number in which probes are located; only needed if probes spanned multiple chromosomes |
lambda1 |
smoothing parameter for the Cauchy component |
lambda2 |
smoothing parameter for the Normal component, must be greater than 0. |
K |
determine fold of cross validation. |
A list with the following components
lambda1 |
smoothing parameter for the Cauchy component |
lambda2 |
smoothing parameter for the Normal component |
err.rates |
the error rates achieved. |
Huang Jian and Agus Salim
Huang, J., Lei, K., Salim, A., O'Sullivan, K., Pawitan, Y. Classification of array CGH data using smoothed logistic regression model. submitted
# example using oral squamous-cell carcinoma data, chromosome 10 only data(oscc) data(phenoscc) Z <- oscc[oscc$Chrom==10,6:80] y <- phenoscc$p53[!is.na(phenoscc$p53)] out <- cv.lambda(y=y,Z=Z,Chrom=oscc$Chrom[oscc$Chrom==10],lambda1=exp(10),lambda2=exp(10)) print(out)