bootstrap.lvm: Calculate bootstrap estimates of a lvm object

In kkholst/lava: Latent Variable Models

Calculate bootstrap estimates of a lvm object

Description

Draws non-parametric bootstrap samples

Usage

## S3 method for class 'lvm'
bootstrap(x,R=100,data,fun=NULL,control=list(),
                          p, parametric=FALSE, bollenstine=FALSE,
                          constraints=TRUE,sd=FALSE, mc.cores,
                          future.args=list(future.seed=TRUE),
                          ...)

## S3 method for class 'lvmfit'
bootstrap(x,R=100,data=model.frame(x),
                             control=list(start=coef(x)),
                             p=coef(x), parametric=FALSE, bollenstine=FALSE,
                             estimator=x$estimator,weights=Weights(x),...)

Arguments

x	lvm-object.
R	Number of bootstrap samples
data	The data to resample from
fun	Optional function of the (bootstrapped) model-fit defining the statistic of interest
control	Options to the optimization routine
p	Parameter vector of the null model for the parametric bootstrap
parametric	If TRUE a parametric bootstrap is calculated. If FALSE a non-parametric (row-sampling) bootstrap is computed.
bollenstine	Bollen-Stine transformation (non-parametric bootstrap) for bootstrap hypothesis testing.
constraints	Logical indicating whether non-linear parameter constraints should be included in the bootstrap procedure
sd	Logical indicating whether standard error estimates should be included in the bootstrap procedure
mc.cores	Optional number of cores for parallel computing. If omitted future.apply will be used (see future::plan)
future.args	arguments to future.apply::future_lapply
...	Additional arguments, e.g. choice of estimator.
estimator	String definining estimator, e.g. 'gaussian' (see estimator)
weights	Optional weights matrix used by estimator

Value

A bootstrap.lvm object.

Author(s)

Klaus K. Holst

See Also

confint.lvmfit

Examples

m <- lvm(y~x)
d <- sim(m,100)
e <- estimate(lvm(y~x), data=d)
 ## Reduce Ex.Timings
B <- bootstrap(e,R=50,mc.cores=1)
B

kkholst/lava documentation built on Feb. 22, 2024, 4:07 p.m.