mpath (version 0.3-7)

cv.glmreg: Cross-validation for glmreg

Description

Does k-fold cross-validation for glmreg, produces a plot, and returns cross-validated log-likelihood values for lambda

Usage

# S3 method for formula
cv.glmreg(formula, data, weights, offset=NULL, ...)
# S3 method for matrix
cv.glmreg(x, y, weights, offset=NULL, ...)
# S3 method for default
cv.glmreg(x,  ...)
# S3 method for cv.glmreg
plot(x,se=TRUE,ylab=NULL, main=NULL, width=0.02, col="darkgrey", ...)
# S3 method for cv.glmreg
predict(object, newx, ...)
# S3 method for cv.glmreg
coef(object,which=object$lambda.which, ...)

Arguments

formula

symbolic description of the model, see details.

data

argument controlling formula processing via model.frame.

x

x matrix as in glmreg. It could be object of cv.glmreg.

y

response y as in glmreg.

weights

Observation weights; defaults to 1 per observation

offset

Not implemented yet

object

object of cv.glmreg

newx

Matrix of values at which predictions are to be made. Not used for type="coefficients"

which

Indices of the penalty parameter lambda at which estimates are extracted. By default, the one which generates the optimal cross-validation value.

se

logical value, if TRUE, standard error curve is also plotted

ylab

ylab on y-axis

main

title of plot

width

width of lines

col

color of standard error curve

…

Other arguments that can be passed to glmreg.

Value

an object of class "cv.glmreg" is returned, which is a list with the ingredients of the cross-validation fit.

fit

a fitted glmreg object for the full data.

residmat

matrix of log-likelihood values with row values for lambda and column values for kth cross-validation

bic

matrix of BIC values with row values for lambda and column values for kth cross-validation

cv

The mean cross-validated log-likelihood values - a vector of length length(lambda).

cv.error

estimate of standard error of cv.

foldid

an optional vector of values between 1 and nfold identifying what fold each observation is in.

lambda

a vector of lambda values

lambda.which

index of lambda that gives maximum cv value.

lambda.optim

value of lambda that gives maximum cv value.

Details

The function runs glmreg nfolds+1 times; the first to compute the lambda sequence, and then to compute the fit with each of the folds omitted. The error or the log-likelihood value is accumulated, and the average value and standard deviation over the folds is computed. Note that cv.glmreg can be used to search for values for alpha: it is required to call cv.glmreg with a fixed vector foldid for different values of alpha.

References

Zhu Wang, Shuangge Ma, Michael Zappitelli, Chirag Parikh, Ching-Yun Wang and Prasad Devarajan (2014) Penalized Count Data Regression with Application to Hospital Stay after Pediatric Cardiac Surgery, Statistical Methods in Medical Research. 2014 Apr 17. [Epub ahead of print]

See Also

glmreg and plot, predict, and coef methods for "cv.glmreg" object.

Examples

# NOT RUN {
data("bioChemists", package = "pscl")
fm_pois <- cv.glmreg(art ~ ., data = bioChemists, family = "poisson")
title("Poisson Family",line=2.5)
predict(fm_pois, newx=bioChemists)
coef(fm_pois)
# }