summary.cv.biglasso: Summarizing inferences based on cross-validation

In YaohuiZeng/biglasso: Extending Lasso Model Fitting to Big Data

Summarizing inferences based on cross-validation

Description

Summary method for cv.biglasso objects.

Usage

## S3 method for class 'cv.biglasso'
summary(object, ...)

## S3 method for class 'summary.cv.biglasso'
print(x, digits, ...)

Arguments

object	A cv.biglasso object.
...	Further arguments passed to or from other methods.
x	A "summary.cv.biglasso" object.
digits	Number of digits past the decimal point to print out. Can be a vector specifying different display digits for each of the five non-integer printed values.

Value

summary.cv.biglasso produces an object with S3 class "summary.cv.biglasso". The class has its own print method and contains the following list elements:

penalty	The penalty used by biglasso.
model	Either "linear" or "logistic", depending on the family option in biglasso.
n	Number of observations
p	Number of regression coefficients (not including the intercept).
min	The index of lambda with the smallest cross-validation error.
lambda	The sequence of lambda values used by cv.biglasso.
cve	Cross-validation error (deviance).
r.squared	Proportion of variance explained by the model, as estimated by cross-validation.
snr	Signal to noise ratio, as estimated by cross-validation.
sigma	For linear regression models, the scale parameter estimate.
pe	For logistic regression models, the prediction error (misclassification error).

Author(s)

Yaohui Zeng and Patrick Breheny

See Also

biglasso(), cv.biglasso(), plot.cv.biglasso(), biglasso-package

Examples

## See examples in "cv.biglasso" and "biglasso-package"

YaohuiZeng/biglasso documentation built on April 23, 2024, 4:54 a.m.