LorenzRegression (version 2.2.0)

confint.PLR_boot: Confidence intervals for the penalized Lorenz regression

Description

Provides bootstrap confidence intervals for the explained Gini coefficient and Lorenz-\(R^2\) for an object of class "PLR_boot".

Usage

# S3 method for PLR_boot
confint(
  object,
  parm = c("Gini", "LR2"),
  level = 0.95,
  type = c("norm", "basic", "perc"),
  pars.idx = "BIC",
  bias.corr = TRUE,
  ...
)

Value

A vector providing the desired confidence interval.

Arguments

object

An object of class "PLR_boot". The object might also have S3 class "PLR_cv". The current implementation requires bootstrap to construct confidence intervals. Hence, it is not sufficient that object inherits from "PLR".

parm

A character string determining whether the confidence interval is computed for the explained Gini coefficient or for the Lorenz-\(R^2\). Possible values are "Gini" (default, for the explained Gini) and "LR2" (for the Lorenz-\(R^2\))

level

A numeric giving the level of the confidence interval. Default value is 0.95.

type

A character string specifying the bootstrap method. Possible values are "norm", "basic" and "perc". For more information, see the argument type of the function boot.ci from the boot library.

pars.idx

What grid and penalty parameters should be used for parameter selection. Either a character string specifying the selection method, where the possible values are:

• "BIC" (default).

• "Boot".

• "CV" - Available if object inherits from "PLR_cv".

Or a numeric vector of length 2, where the first element is the index of the grid parameter and the second is the index of the penalty parameter.

bias.corr

A logical determining whether bias correction should be performed. Only used if type="norm". Default is TRUE.

...

Additional arguments.

See Also

Lorenz.boot, boot.ci

Examples

## For examples see example(Lorenz.boot)