Description Usage Arguments Details Value Author(s) References See Also Examples
Partial Least Squares (PLS) via TExPosition.
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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. |
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).
See epGPCA
(and also 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 |
Derek Beaton
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.
corePCA
, epPCA
, epGPCA
, tepBADA
, tepGPLS
, tepPLSCA
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