predict.asm: Predict new responses using an 'asm' regression model.

In asm: Optimal Convex M-Estimation for Linear Regression via Antitonic Score Matching

Predict new responses using an asm regression model.

Description

Outputs predictions on new test data based on a fitted asm regression model. Also returns a confidence interval around the conditional mean (if interval = "confidence") or predicted response (if interval = "prediction").

Usage

## S3 method for class 'asm'
predict(object, newdata = NULL, interval = "none", level = 0.95, ...)

Arguments

object	asm object
newdata	new data frame
interval	type of interval calculation, either "none", "confidence" or "prediction". Default is "none".
level	confidence level
...	additional arguments to ensure compatibility with the generic function predict()

Value

matrix of predicted values * if interval = "none", the matrix has one column of predicted values * if interval = "confidence" or "prediction", the matrix has three columns: predicted value, lower bound, and upper bound

Examples

model = asm(mpg ~ cyl + hp + disp, data=mtcars)
predict(model, newdata = data.frame(cyl = 4, hp = 121, disp = 80), interval = "prediction")

n <- 1000
X <- rnorm(n)
beta <- 2
Y <- beta*X + rt(n,df=3)
Mod <- asm(Y ~ X)
predict(Mod, newdata = data.frame(X = 1), interval = "prediction")

asm documentation built on April 12, 2025, 1:41 a.m.