predict.PLR {LorenzRegression} | R Documentation |
Prediction and fitted values for the penalized Lorenz regression
Description
predict
provides predictions for an object of class "PLR"
,
while fitted
extracts the fitted values.
Usage
## S3 method for class 'PLR'
predict(object, newdata, type = c("index", "response"), pars.idx = "BIC", ...)
## S3 method for class 'PLR'
fitted(object, type = c("index", "response"), pars.idx = "BIC", ...)
Arguments
object |
An object of S3 class |
newdata |
An optional data frame in which to look for variables with which to predict. If omitted, the original data are used. |
type |
A character string indicating the type of prediction or fitted values. Possible values are |
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:
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. |
... |
Additional arguments passed to the function |
Details
The type
argument distinguishes between two types of prediction outputs, aligned with the goals of the penalized Lorenz regression.
When type = "index"
, the function returns the estimated index X^\top \theta
of the single-index model. This index captures the full ordering structure of the conditional expectation and is sufficient for computing the explained Gini coefficient, which is the primary focus of the method. Crucially, this estimation does not require recovering the full nonparametric link function.
When type = "response"
, the function estimates the full conditional expectation \mathbb{E}[Y | X]
by performing a second-stage estimation of the link function via Rearrangement.estimation
. This is useful if fitted or predicted response values are needed for other purposes.
Value
A vector of predictions for predict
, or a vector of fitted values for fitted
.
See Also
Lorenz.Reg
, Rearrangement.estimation
Examples
## For examples see example(Lorenz.Reg), example(Lorenz.boot) and example(PLR.CV)