tepPLS {TExPosition} | R Documentation |
Partial Least Squares
Description
Partial Least Squares (PLS) via TExPosition.
Usage
tepPLS(
DATA1,
DATA2,
center1 = TRUE,
scale1 = "SS1",
center2 = TRUE,
scale2 = "SS1",
DESIGN = NULL,
make_design_nominal = TRUE,
graphs = TRUE,
k = 0
)
Arguments
DATA1 |
Data matrix 1 (X) |
DATA2 |
Data matrix 2 (Y) |
center1 |
a boolean, vector, or string to center |
scale1 |
a boolean, vector, or string to scale |
center2 |
a boolean, vector, or string to center |
scale2 |
a boolean, vector, or string to scale |
DESIGN |
a design matrix to indicate if rows belong to groups. |
make_design_nominal |
a boolean. If TRUE (default), DESIGN is a vector that indicates groups (and will be dummy-coded). If FALSE, DESIGN is a dummy-coded matrix. |
graphs |
a boolean. If TRUE (default), graphs and plots are provided
(via |
k |
number of components to return. |
Details
This implementation of Partial Least Squares is a symmetric analysis. It was first described by Tucker (1958), again by Bookstein (1994), and has gained notoriety in Neuroimaging from McIntosh et al., (1996).
Value
See corePCA
for details on what is returned. In
addition to the values returned:
lx |
latent variables from DATA1 computed for observations |
ly |
latent variables from DATA2 computed for observations |
data1.norm |
center and scale information for DATA1 |
data1.norm |
center and scale information for DATA2 |
Author(s)
Derek Beaton
References
Tucker, L. R. (1958). An inter-battery method of factor
analysis. Psychometrika, 23(2), 111–136.
Bookstein, F.,
(1994). Partial least squares: a dose–response model for measurement in the
behavioral and brain sciences. Psycoloquy 5 (23)
McIntosh,
A. R., Bookstein, F. L., Haxby, J. V., & Grady, C. L. (1996). Spatial
Pattern Analysis of Functional Brain Images Using Partial Least Squares.
NeuroImage, 3(3), 143–157.
Krishnan, A., Williams, L. J., McIntosh, A. R., & Abdi, H. (2011). Partial
Least Squares (PLS) methods for neuroimaging: A tutorial and review.
NeuroImage, 56(2), 455 – 475.
McIntosh, A. R., &
Lobaugh, N. J. (2004). Partial least squares analysis of neuroimaging data:
applications and advances. Neuroimage, 23, S250–S263.
See Also
corePCA
, epPCA
, tepBADA
,
tepPLSCA
Examples
data(beer.tasting.notes)
data1<-beer.tasting.notes$data[,1:8]
data2<-beer.tasting.notes$data[,9:16]
pls.res <- tepPLS(data1,data2)