plot.spls: Plot the coefficient path of SPLS regression

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

Description

Provide the coefficient path plot of SPLS regression as a function of the number of hidden components (K) when eta is fixed.

Usage

## S3 method for class 'spls'
plot( x, yvar=c(1:ncol(x$y)), ... )

Arguments

x	A fitted SPLS object.
yvar	Index vector of responses to be plotted.
...	Other parameters to be passed through to generic plot.

Details

plot.spls provides the coefficient path plot of SPLS fits. The plot shows how estimated coefficients change as a function of the number of hidden components (K), when eta is fixed at the value used by the original SPLS fit.

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

print.spls, predict.spls, and coef.spls.

Examples

data(yeast)
# SPLS with eta=0.7 & 8 hidden components
f <- spls( yeast$x, yeast$y, K=8, eta=0.7 )
# Draw coefficient path plots for the first two responses
plot( f, yvar=c(1:2) )

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.