plsdepot (version 0.1.17)

simplsca: SIMPLS-CA: SIMPLS Canonical Analysis

Description

The function simplsca performs the SIMPLS Canonical Analysis algorithm as described in Michel Tenenhaus book La Regression PLS, chapter 5.

Usage

simplsca(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 "simplsca", 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.scores

scores of the Y-block (also known as U components)

y.wgs

weights of the Y-block

cor.xt

correlations between X and T

cor.yu

correlations between Y and U

cor.xu

correlations between X and U

cor.yt

correlations between Y and T

cor.tu

correlations between T and U

R2XT

explained variance of X by T

R2YT

explained variance of Y by T

R2YU

explained variance of Y by U

R2XU

explained variance of X by U

Details

No missing data are allowed.

References

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

See Also

plot.simplsca, simpls

Examples

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