RVmldea: This function implement the maximum likelihood approach of...

In hychen-uic/TEV: Total Explained Variation

This function implement the maximum likelihood approach of Dicker and Erdogdu (2016).

Description

This the mle for the high dimensional linear model

Usage

RVmldea(y, x, alpha = c(0.05), lam = 1, niter = 100, eps = 1e-06)

Arguments

y	outcome: a vector of length n.
x	covariates: a matrix of nxp dimension.
alpha	a vector of type I errors used to generate (1-alpha)confidence intervals.
lam	initial value
niter	the number of iterations for finding the signal noise ratio
eps	the convergence criterion for the iteration

Details

This method assume the independent covariates with fixed effects but can be equivalently treated as random effects

Value

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

References

Dicker, L. H. and Erdogdu, M. A. (2016). Maximum likelihood for variance estimation in high-dimensional linear models. Proceedings of the 19th International Conference on Articial Intelligence and Statistics

Examples

## Not run: RVMLE(y,x)

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