ci.spls: Calculate bootstrapped confidence intervals of SPLS coefficients

Description

Calculate bootstrapped confidence intervals of coefficients of the selected predictors and generate confidence interval plots.

Usage

ci.spls( object, coverage=0.95, B=1000,
        plot.it=FALSE, plot.fix="y",
        plot.var=NA, K=object$K, fit=object$fit )

Arguments

object

A fitted SPLS object.

coverage

Coverage of confidence intervals. coverage should have a number between 0 and 1. Default is 0.95 (95$%$ confidence interval).

Number of bootstrap iterations. Default is 1000.

plot.it

Plot confidence intervals of coefficients?

plot.fix

If plot.fix="y", then plot confidence intervals of the predictors for a given response. If plot.fix="x", then plot confidence intervals of a given predictor across all the respon

plot.var

Index vector of responses (if plot.fix="y") or predictors (if plot.fix="x") to be fixed in plot.fix. The indices of predictors are defined among the set of the sel

Number of hidden components. Default is to use the same K as in the original SPLS fit.

fit

PLS algorithm for model fitting. Alternatives are "kernelpls", "widekernelpls", "simpls", or "oscorespls". Default is to use the same PLS al

Value

Invisibly returns a list with components:
cibetaA list with as many matrix elements as the number of responses. Each matrix element is p by 2, where i-th row of the matrix lists the upper and lower bounds of the bootstrapped confidence interval of the i-th predictor.
betahatMatrix of original coefficients of the SPLS fit.
lbmatMatrix of lower bounds of confidence intervals (for internal use).
ubmatMatrix of upper bounds of confidence intervals (for internal use).

References

Chun H and Keles S (2010), "Sparse partial least squares for simultaneous dimension reduction and variable selection", Journal of the Royal Statistical Society - Series B, Vol. 72, pp. 3--25.

Examples

Run this code

data(mice)
# SPLS with eta=0.6 & 1 hidden components
f <- spls( mice$x, mice$y, K=1, eta=0.6 )
# Calculate confidence intervals of coefficients
ci.f <- ci.spls( f, plot.it=TRUE, plot.fix="x", plot.var=20 )
# Bootstrapped confidence intervals
cis <- ci.f$cibeta
cis[[20]]   # equivalent, 'cis$1422478_a_at'