sommer (version 4.4.4)

ism: identity covariance structure

Description

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

Usage

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

Value

$res

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

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

Author

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 vsm to know how to use ism in the mmes solver.

Examples

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

# data(DT_example, package="enhancer")
# ans1 <- mmes(Yield~Env,
#              random= ~ vsm( ism( Name ) ),
#              data=DT_example)
# summary(ans1)$varcomp