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grpss (version 3.0.1)

print.summary.cv.grpreg: Summarize a fitted cv.grpreg object

Description

Summarizes a fitted penalized regression model with 'cv.grpreg' class.

Usage

"print"(x, digits = 4, ...)

Arguments

x
A "summary.cv.grpreg" object.
digits
Number of digits past the decimal point to print out. The default is 4.
...
Optional arguments passed to other methods.

Value

A list with class "summary.cv.grpreg" containing the following components:
n
Number of observations.
p
Number of screened predictors.
penalty
The penalty applied to the model.
model
The type of model.
family
The link function.
criterion
The screening criterion.
lambda
The default or specified regularization parameter.
beta
The estimates of coefficients at the specified lambda.
iter
The number of iterations at the specified lambda.
df
The estimates of effective number of model parameters at the specified lambda.
call
The function call.
Additional elements are contained for the case in which family = "gaussian":
r.squared
The r.squared.
snr
The signal-to-noise ratio.
scale
The scale parameter estimate (sigma).
and following elements for the case in which family = "poisson" or "binomial":
logLik
The negative log-likelihood values for the fitted model.
aic
Akaike's information criterion (AIC).
bic
Bayesian information criterion (BIC).
aicc
The AIC with a correction for finite sample sizes (AICC).
pe
The prediction error for family = "binomial".

Details

This function is similar to summary.cv.grpreg in grpreg package, but gives several different results. The lambda here is only valid for "grpreg" object. See summary.grpreg.

See Also

grpss, summary.grpreg