coefplot.spls: Plot estimated coefficients of the SPLS object

In spls: Sparse Partial Least Squares (SPLS) Regression and Classification

Description

Plot estimated coefficients of the selected predictors in the SPLS object.

Usage

coefplot.spls( object, nwin=c(2,2),
            xvar=c(1:length(object$A)), ylimit=NA )

Arguments

object	A fitted SPLS object.
nwin	Vector of the number of rows and columns in a plotting area. Default is two rows and two columns, i.e., four plots.
xvar	Index of variables to be plotted among the set of the selected predictors. Default is to plot the coefficients of all the selected predictors.
ylimit	Range of the y axis (the coefficients) in the plot. If ylimit is not specified, the y axis of the plot has the range between the minimum and the maximum of all coefficient estimates.

Details

This plot is useful for visualizing coefficient estimates of a variable for different responses. Hence, the function is applicable only with multivariate response SPLS.

Value

NULL.

Author(s)

Dongjun Chung, Hyonho Chun, and Sunduz Keles.

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.

See Also

ci.spls, and correct.spls and plot.spls.

Examples

data(yeast)
# SPLS with eta=0.7 & 8 hidden components
f <- spls( yeast$x, yeast$y, K=8, eta=0.7 )
# Draw estimated coefficient plot of the first four variables
# among the selected predictors
coefplot.spls( f, xvar=c(1:4), nwin=c(2,2) )

Example output

Sparse Partial Least Squares (SPLS) Regression and
Classification (version 2.2-3)

spls documentation built on May 6, 2019, 1:09 a.m.