FULLREML: This function implement the maximum likelihood approach with...

In hychen-uic/TEV: Total Explained Variation

This function implement the maximum likelihood approach with variance estimated by inverse of information matrix.

Description

This is the reml for the high dimensional linear model

Usage

FULLREML(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

Restricted maximum likelihood estimator of the random effects model

Examples

## Not run: FULLREML(y,x)

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