spls v2.2-3


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Sparse Partial Least Squares (SPLS) Regression and Classification

Provides functions for fitting a sparse partial least squares (SPLS) regression and classification (Chun and Keles (2010) <doi:10.1111/j.1467-9868.2009.00723.x>).

Functions in spls

Name Description
cv.spls Compute and plot cross-validated mean squared prediction error for SPLS regression
prostate Prostate Tumor Gene Expression Dataset
plot.spls Plot the coefficient path of SPLS regression
predict.sgpls Make predictions or extract coefficients from a fitted SGPLS model
print.spls Print function for a SPLS object
print.sgpls Print function for a SGPLS object
sgpls Fit SGPLS classification models
yeast Yeast Cell Cycle Dataset
spls-internal Internal SPLS functions
predict.spls Make predictions or extract coefficients from a fitted SPLS model
spls Fit SPLS regression models
lymphoma Lymphoma Gene Expression Dataset
splsda Fit SPLSDA classification models
mice Mice Dataset
predict.splsda Make predictions or extract coefficients from a fitted SPLSDA model
print.splsda Print function for a SPLSDA object
cv.splsda Compute and plot cross-validated error for SPLSDA classification
ci.spls Calculate bootstrapped confidence intervals of SPLS coefficients
coefplot.spls Plot estimated coefficients of the SPLS object
correct.spls Correct the initial SPLS coefficient estimates based on bootstrapped confidence intervals
cv.sgpls Compute and plot the cross-validated error for SGPLS classification
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Last month downloads


Date 2019-05-04
License GPL (>= 2)
NeedsCompilation no
Packaged 2019-05-04 21:53:24 UTC; Share
Repository CRAN
Date/Publication 2019-05-04 23:10:03 UTC

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