ranef: Extract Random Effects

In ggmix: Variable Selection in Linear Mixed Models for SNP Data

Description

Generic function for extracting the random effects. This is the same generic (and same name) defined in the nlme and lme4 package.

Usage

ranef(object, ...)

random.effects(object, ...)

## Default S3 method:
random.effects(object, ...)

## Default S3 method:
ranef(object, ...)

## S3 method for class 'ggmix_gic'
ranef(object, s = "lambda.min", ...)

Arguments

object	any fitted model object from which random effects estimates can be extracted. Currently supports "ggmix_gic" objects outputted by the gic function
...	other parameters. currently ignored
s	Value(s) of the penalty parameter lambda at which predictions are required. Default is the value s="lambda.min" can be used. If s is numeric, it is taken as the value(s) of lambda to be used.

Details

For objects of class "ggmix_gic", this function returns the subject-specific random effect value for the model which minimizes the GIC using the maximum a posteriori principle

Value

a numeric vector of length equal to the number of observations of subject-specific random effects

See Also

gic

Examples

data("admixed")
fit <- ggmix(x = admixed$xtrain, y = admixed$ytrain,
            kinship = admixed$kin_train)
gicfit <- gic(fit)
# random effect at selected value of lambda
plot(ggmix::ranef(gicfit))
# random effects at specific values of lambda
head(ggmix::ranef(gicfit, s = c(0.1,0.2)))

ggmix documentation built on April 13, 2021, 9:06 a.m.