plsgmd: Partial least squares with the generalized matrix...
In pknight24/plsgmd: Partial least squares with the generalized matrix decomposition
Description
Usage
Arguments
Value
Description
Partial least squares with the generalized matrix decomposition
Usage
1
Arguments
X
The n by p data matrix of predictors
Y
The n by q matrix of outcomes
H
An n by n sample-wise similarity matrix.
Q1
A p by p similarity matrix of the features in X.
Q2
A q by q similarity matrix corresponding to columns in Y.
k
Integer, the number of PLS latent variables to compute.
Value
Scores and loadings for X and Y.
pknight24/plsgmd documentation built on Feb. 8, 2021, 1:20 a.m.
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Description Usage Arguments Value
Description
Partial least squares with the generalized matrix decomposition
Usage
1 |
Arguments
X |
The n by p data matrix of predictors |
Y |
The n by q matrix of outcomes |
H |
An n by n sample-wise similarity matrix. |
Q1 |
A p by p similarity matrix of the features in X. |
Q2 |
A q by q similarity matrix corresponding to columns in Y. |
k |
Integer, the number of PLS latent variables to compute. |
Value
Scores and loadings for X and Y.
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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