cv.lambda {slr}R Documentation

Cross-validation for Smoothed Logistic Regression

Description

K-fold Cross Validation for Smoothed Logistic Regression

Usage

cv.lambda(y,Z,Chrom=NULL,lambda1,lambda2,K=10)

Arguments

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.

Value

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.

Author(s)

Huang Jian and Agus Salim

References

Huang, J., Lei, K., Salim, A., O'Sullivan, K., Pawitan, Y. Classification of array CGH data using smoothed logistic regression model. submitted

See Also

slr, oscc, phenoscc

Examples

# 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)

[Package slr version 0.1.9 Index]