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

In 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).

See Also

biglasso(), cv.biglasso(), plot.cv.biglasso()

biglasso documentation built on Aug. 25, 2026, 5:08 p.m.