confints.bootpls: Bootstrap confidence intervals

In plsRglm: Partial Least Squares Regression for Generalized Linear Models

Bootstrap confidence intervals

Description

This function is a wrapper for boot.ci to derive bootstrap-based confidence intervals from a "boot" object.

Usage

confints.bootpls(bootobject, indices = NULL, typeBCa = TRUE)

Arguments

bootobject	an object of class "boot"
indices	the indices of the predictor for which CIs should be calculated. Defaults to NULL: all the predictors will be used.
typeBCa	shall BCa bootstrap based CI derived ? Defaults to TRUE. This is a safety option since sometimes computing BCa bootstrap based CI fails whereas the other types of CI can still be derived.

Value

Matrix with the limits of bootstrap based CI for all (defaults) or only the selected predictors (indices option). The limits are given in that order: Normal Lower then Upper Limit, Basic Lower then Upper Limit, Percentile Lower then Upper Limit, BCa Lower then Upper Limit. Column names are added so that the returned matrix can be reused by downstream helpers such as confints2signifind.

Author(s)

Frédéric Bertrand
[e-mail]
https://fbertran.github.io/homepage/

See Also

See also bootpls and bootplsglm.

Examples

data(Cornell)

#Lazraq-Cleroux PLS (Y,X) bootstrap
set.seed(250)
modpls <- plsR(Y~.,data=Cornell,3)
Cornell.bootYX <- bootpls(modpls, R=250, verbose=FALSE)
confints.bootpls(Cornell.bootYX,2:8)
confints.bootpls(Cornell.bootYX,2:8,typeBCa=FALSE)

plsRglm documentation built on June 17, 2026, 5:06 p.m.