estimate.vc: REML EM Algorithm

In SEAGLE: Scalable Exact Algorithm for Large-Scale Set-Based Gene-Environment Interaction Tests

Description

REML EM algorithm for estimating variance components

Usage

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

SEAGLE documentation built on Nov. 6, 2021, 1:06 a.m.