tune.cosso: Tuning procedure for cosso

In cosso: Fit Regularized Nonparametric Regression Models Using COSSO Penalty

Tuning procedure for cosso

Description

Compute K-fold cross-validated score and plot cross-validated score against a grid values of smooth parameter M.

Usage

 
tune.cosso(object,folds=5,plot.it=TRUE)   

Arguments

object	a cosso object.
folds	number of folds for corss-validation. Default is 5. It is not recommended to use folds less than 4.
plot.it	if TRUE, plot the cross-validated score against a sequence values of M.

Value

OptM	the optimal smoothing parameter for M.
M	used tuning grid points.
cvm	the mean cross-validated error/minus log-likelihood.
cvsd	estimate of standard error of cvm.

Author(s)

Hao Helen Zhang and Chen-Yen Lin

See Also

cosso, predict.cosso

Examples

 
## Binomial
set.seed(20130310)
x=cbind(rbinom(150,1,.7),matrix(runif(150*5,0,1),nc=5))
trueProb=1/(1+exp(-x[,1]-sin(2*pi*x[,2])-5*(x[,4]-0.4)^2))
y=rbinom(150,1,trueProb)

B.Obj=cosso(x,y,family="Bin",nbasis=30) 
tune.cosso(B.Obj,4,TRUE)

cosso documentation built on March 31, 2023, 8:25 p.m.