# confints.bootpls

From plsRglm v1.2.5
by Frederic Bertrand

##### Bootstrap confidence intervals

This function is a wrapper for `boot.ci`

to derive bootstrap-based confidence intervals from a `"boot"`

object.

- Keywords
- models, regression

##### 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.

##### See Also

See also `bootpls`

and `bootplsglm`

.

##### Examples

```
# NOT RUN {
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)
# }
```

*Documentation reproduced from package plsRglm, version 1.2.5, License: GPL-3*

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