A summary function for cv_plmm objects

A summary function for cv_plmm objects

Usage

# S3 method for class 'cv_plmm'
summary(object, lambda = "min", ...)

Arguments

object

A cv_plmm object

lambda

The regularization parameter value at which inference should be reported. Can choose a numeric value, 'min', or '1se'. Defaults to 'min.'

...

Not used

Value

The return value is an object with S3 class summary.cv_plmm. The class has its own print method and contains the following list elements:

• lambda_min: The lambda value at the minimum cross validation error

• lambda.1se: The maximum lambda value within 1 standard error of the minimum cross validation error

• penalty: The penalty applied to the fitted model

• nvars: The number of non-zero coefficients at the selected lambda value

• cve: The cross validation error at all folds

• min: The minimum cross validation error

• fit: The plmm fit used in the cross validation

if returnBiasDetails = TRUE, two more items are returned:

• bias: The mean bias of the cross validation

• loss: The loss at each value of lambda

Examples

admix_design <- create_design(X = admix$X, outcome_col = admix$y)
cv_fit <- cv_plmm(design = admix_design)
summary(cv_fit)
#> lasso-penalized model with n=197 and p=101
#> At minimum cross-validation error (lambda=0.2249):
#> -------------------------------------------------
#>   Nonzero coefficients: 6
#>   Cross-validation error (deviance): 2.12
#>   Scale estimate (sigma): 1.456