predict.islasso: Prediction Method for islasso Objects

In islasso: The Induced Smoothed Lasso

Prediction Method for islasso Objects

Description

Computes predictions from a fitted islasso model object. Multiple output types supported, including response scale, linear predictor, and coefficient values.

Usage

## S3 method for class 'islasso'
predict(
  object,
  newdata = NULL,
  type = c("link", "response", "coefficients", "class", "terms"),
  se.fit = FALSE,
  ci = NULL,
  type.ci = c("wald", "score"),
  level = 0.95,
  terms = NULL,
  na.action = na.pass,
  ...
)

Arguments

object	A fitted model of class "islasso".
newdata	Optional data frame containing predictors for prediction. If omitted, the fitted model matrix is used.
type	Character. Specifies the prediction scale: "link" (default): linear predictor scale; "response": original response scale; "coefficients": estimated coefficients; "class": predicted class (only for binomial() family); "terms": contribution of each term to the linear predictor.
se.fit	Logical. Whether to compute standard errors/confidence intervals.
ci	Optional. Precomputed matrix of confidence intervals (2 columns).
type.ci	Type of interval. Only "wald" is implemented.
level	Confidence level for intervals. Default is 0.95.
terms	If type = "terms", optionally specify which terms to extract.
na.action	Function to handle missing values in newdata. Default: na.pass.
...	Additional arguments passed to downstream methods.

Value

A numeric vector, matrix, or list depending on type.

Author(s)

Gianluca Sottile [e-mail]

See Also

islasso, summary.islasso, logLik.islasso, residuals.islasso, deviance.islasso

Examples

set.seed(1)
n <- 100; p <- 100
beta <- c(runif(20, -3, 3), rep(0, p - 20))
sim <- simulXy(n = n, p = p, beta = beta, seed = 1, family = gaussian())
fit <- islasso(y ~ ., data = sim$data, family = gaussian(), lambda = 2)
predict(fit, type = "response")

islasso documentation built on Aug. 9, 2025, 1:06 a.m.