isc: identity covariance structure

In sommer: Solving Mixed Model Equations in R

identity covariance structure

Description

isc creates an identity covariance structure for the levels of the random effect to be used with the mmec solver. Any random effect with a special covariance structure should end with an isc() structure.

Usage

  isc(x, thetaC=NULL, theta=NULL)

Arguments

x	vector of observations for the random effect.
thetaC	an optional 1 x 1 matrix for constraints in the variance-covariance components. The values in the matrix define how the variance-covariance components should be estimated: 0: component will not be estimated 1: component will be estimated and constrained to be positive (default) 2: component will be estimated and unconstrained 3: component will be fixed to the value provided in the theta argument
theta	an optional 1 x 1 matrix for initial values of the variance-covariance component. When providing customized values, these values should be scaled with respect to the original variance. For example, to provide an initial value of 1 to a given variance component, theta would be built as: theta = matrix( 1 / var(response) ) The values in the matrix define the initial values of the variance-covariance components that will be subject to the constraints provided in thetaC. If not provided, initial values (theta) will be 0.15

Value

$res

a list with the provided vector and the variance covariance structure expected for the levels of the random effect.

Author(s)

Giovanny Covarrubias-Pazaran

References

Covarrubias-Pazaran G (2016) Genome assisted prediction of quantitative traits using the R package sommer. PLoS ONE 11(6): doi:10.1371/journal.pone.0156744

See Also

See the function vsc to know how to use isc in the mmec solver.

Examples

x <- as.factor(c(1:5,1:5,1:5));x
isc(x)

# data(DT_example)
# ans1 <- mmec(Yield~Env,
#              random= ~ vsc( isc( Name ) ),
#              data=DT_example)
# summary(ans1)$varcomp

sommer documentation built on Sept. 11, 2024, 6:22 p.m.