REML EM algorithm for estimating variance components

estimate.vc(
y,
Xtilde,
qrXtilde,
beta,
G,
init.sigma = 0.5,
init.tau = 0.5,
tol = 0.001,
maxiters = 1000
)

## Arguments

y Vector of observed phenotypes Matrix of covariates (first column contains the intercept, last column contains the E factor for studying the GxE effect) Object containing QR decomposition of Xtilde Coefficient vector for covariate matrix Xtilde Matrix of genotype markers Initial sigma input (Default is 0.5) Initial tau input (Default is 0.5) Tolerance for convergence (Default is 1e-3) Maximum number of iterations (Default is 1000)

## Value

Estimates for tau and sigma