This function estimates genetic and residual variances, and genetic correlations.
Usage
grmsem.var(grmsem.out = NULL)
Arguments
grmsem.out
A grmsem.fit or grmsem.stpar object. Default NULL.
Value
grmsem.var returns a list object consisting of the following matrices:
VA
estimated genetic variance
VA.se
standard error of estimated genetic variance
VE
estimated residual variance
VE.se
standard error of estimated residual variance
VP
estimated total phenotypic variance
RG
genetic correlation
RG.se
standard error genetic correlation
RE
residual correlation
RG.se
standard error residual correlation
Details
The grmsem.var function can be used to estimate genetic and residual covariance and correlations for DS, Cholesky, IP and IPC models, based on
grmsem.fit or grmsem.stpar objects. For the latter, the diagonal elements of the VA output matrix
detail the heritabilities. Except for directly estimated variance components using the DS model, all standard errors
are derived with the Delta method.
# NOT RUN {#(runtime should be less than one minute)# }# NOT RUN {out <- grmsem.fit(ph.small, G.small, LogL = TRUE, estSE = TRUE)
var.out <- grmsem.var(out)
print(var.out)
# }