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Solves a univariate mixed model of form \(y=X\beta+M_1u_1+M_2u_2+e\) using the Expectation-Maximization algorithm.

Usage

solveRRBLUP_EM2(Y, X, M1, M2, Vu1, Vu2, Ve, tol, maxIter, useEM)

Arguments

Y

a matrix with n rows and 1 column

X

a matrix with n rows and x columns

M1

a matrix with n rows and m1 columns

M2

a matrix with n rows and m2 columns

Vu1

initial guess for variance of the first marker effects

Vu2

initial guess for variance of the second marker effects

Ve

initial guess for error variance

tol

tolerance for declaring convergence

maxIter

maximum iteration for attempting convergence

useEM

should EM algorithm be used. If false, no estimation of variance components is performed. The initial values are treated as true.