boot.plots: Plots of the Output of a Bootstrap Simulation for an...

In mvdalab: Multivariate Data Analysis Laboratory

Plots of the Output of a Bootstrap Simulation for an mvdareg Object

Description

This takes an mvdareg object fitted with validation = "oob" and produces a graph of the bootstrap distribution and its corresponding normal quantile plot for a variable of interest.

Usage

boot.plots(object, comp = object$ncomp, parm = NULL,
           type = c("coefs", "weights", "loadings"))

Arguments

object	an object of class "mvdareg", i.e., a plsFit.
comp	latent variable from which to generate the bootstrap distribution for a specific parameter
parm	a parameter for which to generate the bootstrap distribution
type	input parameter vector

Details

The function generates the bootstrap distribution and normal quantile plot for a bootstrapped mvdareg model given validation = "oob" for type = c("coefs", "weights", "loadings"). If parm = NULL a paramater is chosen at random.

Value

The output of boot.plots is a histogram of the bootstrap distribution and the corresponding normal quantile plot.

Author(s)

Nelson Lee Afanador ([e-mail])

See Also

bca.cis

Examples

data(Penta)
## Number of bootstraps set to 300 to demonstrate flexibility
## Use a minimum of 1000 (default) for results that support bootstraping
mod1 <- plsFit(log.RAI ~., scale = TRUE, data = Penta[, -1],
               ncomp = 2, validation = "oob", boots = 300)
boot.plots(mod1, type = "coefs", parm = NULL)

mvdalab documentation built on Oct. 6, 2022, 1:05 a.m.