correct.spls: Correct the initial SPLS coefficient estimates based on...

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

Description

Correct initial SPLS coefficient estimates of the selected predictors based on bootstrapped confidence intervals and draw heatmap of original and corrected coefficient estimates.

Usage

correct.spls( object, plot.it=TRUE )

Arguments

object	An object obtained from the function ci.spls.
plot.it	Draw the heatmap of original coefficient estimates and corrected coefficient estimates?

Details

The set of the selected variables is updated by setting the coefficients with zero-containing confidence intervals to zero.

Value

Invisibly returns a matrix of corrected coefficient estimates.

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.

Examples

data(mice)
# SPLS with eta=0.6 & 1 latent components
f <- spls( mice$x, mice$y, K=1, eta=0.6 )
# Calculate confidence intervals of coefficients
ci.f <- ci.spls(f)
# Corrected coefficient estimates
cf <- correct.spls( ci.f )
cf[20,1:5]

Example output

Sparse Partial Least Squares (SPLS) Regression and
Classification (version 2.2-1)

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1415889_a_at   1415965_at   1416308_at   1417017_at   1417208_at 
  0.00000000   0.05103286   0.00000000   0.00000000   0.00000000 

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