boot.plots {mvdalab} | R Documentation |
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 |
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 (nelson.afanador@mvdalab.com)
See Also
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)