Internal function of cross-validation for glmreg

Description

Internal function to conduct k-fold cross-validation for glmreg, produces a plot, and returns cross-validated log-likelihood values for lambda

Usage

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cv.glmreg_fit(x, y, weights, lambda=NULL, balance=TRUE, 
family=c("gaussian", "binomial", "poisson", "negbin"), 
nfolds=10, foldid, plot.it=TRUE, se=TRUE, n.cores=2, ...)

Arguments

x

x matrix as in glmreg.

y

response y as in glmreg.

weights

Observation weights; defaults to 1 per observation

lambda

Optional user-supplied lambda sequence; default is NULL, and glmreg chooses its own sequence

balance

for family="binomial" only

family

response variable distribution

nfolds

number of folds >=3, default is 10

foldid

an optional vector of values between 1 and nfold identifying what fold each observation is in. If supplied, nfold can be missing and will be ignored.

plot.it

a logical value, to plot the estimated log-likelihood values if TRUE.

se

a logical value, to plot with standard errors.

n.cores

The number of CPU cores to use. The cross-validation loop will attempt to send different CV folds off to different cores.

...

Other arguments that can be passed to glmreg.

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.

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

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.

fraction

a vector of lambda values with length of lambda

lambda.which

index of lambda that gives maximum cv value.

lambda.optim

value of lambda that gives maximum cv value.

Author(s)

Zhu Wang <zwang@connecticutchildrens.org>

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.

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