Usage
score.calc(M, y, ZO, Hinv, min.MAF, X2, P3D=TRUE, method="AI",
iters=50, R=NULL, REML=TRUE, draw=TRUE)
Arguments
ZO
incidence matrix of random effects
Hinv
inverse of the phenotypic variance matrix
min.MAF
minimum minor allele frequency
X2
incidence matrix X as full rank from eigen decomposition
P3D
When P3D=TRUE, variance components are estimated by REML only once, without any markers in the model. When P3D=FALSE, variance components are estimated by REML for each marker separately. The default is the first case.
method
this refers to the method or algorithm to be used for estimating variance components. The package currently is supported by 3 algorithms; "EMMA" efficient mixed model association (Kang et al. 2008), "AI" average information (Gilmour et al. 1995; Lee et al
iters
a scalar value indicating how many iterations have to be performed if the EM algorithm is selected. There is no rule of tumb for the number of iterations. The default value is 50 iterations or EM steps, but could take less or much longer than that.
R
a matrix for variance-covariance structures for the residuals, i.e. for longitudinal data. if not passed is assumed an identity matrix.
REML
a TRUE/FALSE value indicating if restricted maximum likelihood should be used instead of ML. The default is TRUE.
draw
a TRUE/FALSE value indicating if a plot of updated values for the variance components and the likelihood should be drawn or not. The dafault is TRUE.