LICbeta: Calculate the LIC estimator for linear regression

In COR: The COR for Optimal Subset Selection in Distributed Estimation

Calculate the LIC estimator for linear regression

Description

This function estimates the coefficients of a linear regression model using a design matrix 'X' and a response vector 'Y'. It implements an A-optimal and D-optimal design criteria to choose optimal subsets of observations.

Usage

LICbeta(X, Y, alpha, K, nk)

Arguments

X	The observation matrix (n x p)
Y	The response vector (n x 1)
alpha	The significance level for computing confidence intervals
K	The number of subsets
nk	The number of observations per subset

Value

A list containing:

E5	The LIC estimator for linear regression.

References

Guo, G., Song, H. & Zhu, L. The COR criterion for optimal subset selection in distributed estimation. Statistics and Computing, 34, 163 (2024). \Sexpr[results=rd]{tools:::Rd_expr_doi("10.1007/s11222-024-10471-z")}

COR documentation built on April 4, 2025, 5:13 a.m.