LLIC {LLIC}R Documentation

LLIC for Lre Model

Description

This function carries out an Laplace LIC analysis utilizing the Lre model.

Usage

LLIC(X, y, alpha, K)

Arguments

X

Design matrix

y

Random response vector of observed values

alpha

Significance level

K

Number of subsets

Value

A list containing the following components:

MUopt

A vector of the means of the predictor variables in the optimal subset.

Bopt

A vector of the estimated regression coefficients from the final model fitted to the optimal subset.

MAEMUopt

The Mean Absolute Error (MAE) for the optimal subset.

MSEMUopt

The Mean Squared Error (MSE) for the optimal subset.

opt

Currently NULL, a placeholder for potential future use.

Yopt

A vector of the predicted values from the final model fitted to the optimal subset.

Examples

set.seed(12)
library(VGAM)
X <- matrix(data = sample(1:3, 1200 * 5, replace = TRUE), nrow = 1200, ncol = 5)
b <- sample(1:3, 5, replace = TRUE)
e <- rlaplace(1200, 0, 1)
Y <- X %*% b + e
alpha <- 0.05
K <- 10
result <- LLIC(X, Y, alpha, K)
MUopt <- result$MUopt
Bopt <- result$Bopt
MAEMUopt <- result$MAEMUopt
MSEMUopt <- result$MSEMUopt
opt <- result$opt
Yopt <- result$Yopt


[Package LLIC version 3.0.0 Index]