Description Usage Arguments Details Value References Examples
Performs a constraint sPLS on the first PLS-components and a sPLS on the last components
1 2 3 4 5 6 7 8 9 10 11 | spls.hybrid(X,
Y,
ncomp = 2,
mode = c("regression", "canonical", "invariant", "classic"),
max.iter = 500,
tol = 1e-06,
keepX.constraint,
keepY.constraint,
keepX,
keepY,
near.zero.var = FALSE)
|
X |
numeric matrix of predictors. |
Y |
numeric vector or matrix of responses (for multi-response models).
|
ncomp |
the number of components to include in the model (see Details). Default is 2. |
mode |
character string. What type of algorithm to use.
one of |
max.iter |
integer, the maximum number of iterations. |
tol |
a positive real, the tolerance used in the iterative algorithm. |
keepX.constraint |
A list containing which variables of X are to be kept on each of the first PLS-components. |
keepY.constraint |
A list containing which variables of Y are to be kept on each of the first PLS-components. |
keepX |
number of X variables kept in the model on the last components. |
keepY |
number of Y variables kept in the model on the last components. |
near.zero.var |
boolean, see the internal |
The spls.hybrid
function allows you to compute a constraint spls on the first components and a spls on the last components. Note that the only condition on keepX.constraint
and keepX
is that the sum of both length is ncomp; likewise for the ones relative to Y.
A 'spls.hybrid' object is returned. The object is a list that contains the following components:
X |
the centered and standardized original predictor matrix. |
Y |
the centered and standardized original response vector or matrix. |
ncomp |
the number of components included in the model. |
mode |
the algorithm used to fit the model. |
keepX.constraint |
A list of length |
keepY.constraint |
A list of length |
mat.c |
matrix of coefficients to be used internally by |
variates |
list containing the variates. |
loadings |
list containing the estimated loadings for the X and Y variates. |
names |
list containing the names to be used for individuals and variables. |
nzv |
list containing the zero- or near-zero predictors information, for |
coeff |
A list of means.X, sigma.X, means.Y and sigma.Y. Means and variances for the variables of |
Rohart et al. (2016). A Molecular Classification of Human Mesenchymal Stromal Cells. PeerJ, DOI 10.7717/peerj.1845
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 |
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