plsdepot (version 0.1.17)

simpls: SIMPLS: Alternative Approach to PLS Regression

Description

The function simpls performs the SIMPLS Algorithm as described in Michel Tenenhaus book La Regression PLS, chapter 5.

Usage

simpls(X, Y, comps = 2)

Arguments

X

Numeric matrix or data frame with two or more columns (X-block).

Y

Numeric matrix or data frame with two or more columns (Y-block).

comps

Number of components to be extracted. (TRUE by default).

Value

An object of class "simpls", basically a list with the following elements:

x.scores

scores of the X-block (also known as T components)

x.wgs

weights of the X-block

y.wgs

weights of the Y-block

cor.xt

correlations between X and T

cor.yt

correlations between Y and T

R2X

explained variance of X by T

R2Y

explained variance of Y by T

Details

No missing data are allowed.

References

Tenenhaus, M. (1998) La Regression PLS. Theorie et Pratique. Paris: Editions TECHNIP.

de Jong, S. (1993) SIMPLS: An alternative approach to partial least squares regression. Chemometrics and Intelligent Laboratory Systems, 18: 251-263.

See Also

plot.simpls, simplsca

Examples

## Not run: 
#  # load data linnerud
#  data(linnerud)
# 
#  # apply inter-battery method
#  my_simpls = simpls(linnerud[,1:3], linnerud[,4:6])
# 
#  # plot variables
#  plot(my_simpls, what="variables")
#  ## End(Not run)