coefficients: Extract Summary Information Pertaining to the Coefficients...

In mvdalab: Multivariate Data Analysis Laboratory

Extract Summary Information Pertaining to the Coefficients resulting from a PLS model

Description

Functions to extract regression coefficient bootstrap information from mvdalab objects.

Usage

## S3 method for class 'mvdareg'
coefficients(object, ncomp = object$ncomp, conf = .95, ...)

Arguments

object	an mvdareg object. A fitted model.
ncomp	the number of components to include in the model (see below).
conf	for a bootstrapped model, the confidence level to use.
...	additional arguments. Currently ignored.

Details

coefficients is used to extract a bootstrap summary of the regression of a PLS model.

If comps is missing (or is NULL), summaries for all regression estimates are returned. Otherwise, if comps is given parameters for a model with only the requested component comps is returned.

Boostrap summaries provided are for actual regression coefficients, bootstrap percentiles, bootstrap mean, skewness, and bias. These summaries can also be extracted using coefficients.boots

Value

A coefficients object contains a data frame with columns:

variable	variable names
Actual	Actual loading estimate using all the data
BCa percentiles	confidence intervals
boot.mean	mean of the bootstrap
skewness	skewness of the bootstrap distribution
bias	estimate of bias w.r.t. the loading estimate
Bootstrap Error	estimate of bootstrap standard error
t value	approximate 't-value' based on the Bootstrap Error
bias t value	approximate 'bias t-value' based on the Bootstrap Error

Author(s)

Nelson Lee Afanador ([e-mail])

See Also

coef, coefficients.boots, coefficients

Examples

data(Penta)
mod1 <- plsFit(log.RAI ~., scale = TRUE, data = Penta[, -1],
               ncomp = 2, validation = "loo")
coefficients(mod1)

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