bootstrap.lvm: Calculate bootstrap estimates of a lvm object

In lava: Latent Variable Models

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,silent=FALSE,...)

## 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,weight=Weight(x),...)

Arguments

x	lvm-object.
R	Number of bootstrap samples
fun	Optional function of the (bootstrapped) model-fit defining the statistic of interest
data	The data to resample from
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
estimator	String definining estimator, e.g. 'gaussian' (see estimator)
weight	Optional weight matrix used by estimator
sd	Logical indicating whether standard error estimates should be included in the bootstrap procedure
silent	Suppress messages
...	Additional arguments, e.g. choice of 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(y~x, d)
## Not run: 
B <- bootstrap(e,R=100)
B

## End(Not run)

lava documentation built on May 2, 2019, 4:49 p.m.