REML EM Algorithm

Source: R/em_reml.R

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
Xtilde

Matrix of covariates (first column contains the intercept, last column contains the E factor for studying the GxE effect)
qrXtilde

Object containing QR decomposition of Xtilde
beta

Coefficient vector for covariate matrix Xtilde
G

Matrix of genotype markers
init.sigma

Initial sigma input (Default is 0.5)
init.tau

Initial tau input (Default is 0.5)
tol

Tolerance for convergence (Default is 1e-3)
maxiters

Maximum number of iterations (Default is 1000)

Value

Estimates for tau and sigma