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

Share:

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

1
2
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 fits computes 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

bca.cis

Examples

1
2
3
4
5
6
data(Penta)
## Number of bootstraps set to 500 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 = 500)
boot.plots(mod1, type = "coefs", parm = NULL)

Want to suggest features or report bugs for rdrr.io? Use the GitHub issue tracker.