CHIVE: Estimate the explained variation in high-dimensional linear...

In hychen-uic/TEV: Total Explained Variation

Estimate the explained variation in high-dimensional linear model using the method CHIVE proposed by Cai and Guo (2020)

Description

This function estimates: (1). the proportion of the explained variation (2). the explained variation by covariates in a linear model assuming the covariates have sparse effects.

Usage

CHIVE(y, x, xext = NULL, alpha = c(0.05))

Arguments

y	outcome: a vector of length n.
x	covariates: a matrix of nxp dimension.
xext	supplementary covariates of Nxp dimension.
alpha	confidence level is 100*(1-alpha)%

Details

Both point estimate and confidence intervals are computed.

Value

Estimate of the proportion of explained variation, variance estimates, and confidence intervals.

References

Cai, T. T. Guo, Z. (2020). Semisupervised inference for explained variance in high dimensional linear regression and its applications, Journal of Royal Statistical Society, Ser. B., 82, 391-419.

Examples

## Not run: CHIVE(y,x,lam=0.05)

hychen-uic/TEV documentation built on Jan. 24, 2025, 9:14 p.m.