Bidiagonalization algorithm for PLS1
bidiagpls.fit(X, Y, ncomp, ...)An object of class mvdareg is returned. The object contains all components returned by the underlying fit function. In addition, it contains the following:
X loadings
weights
bidiag2 matrix
inverse of bidiag2 matrix
mean of reponse variable
mean of predictor variables
regression coefficients
y-loadings
X scores
orthogonal weights
scaled response values
actual response values
fitted values
residuals
X matrix
predicted values
scaled y-loadings
model fitting time
validation method
number of latent variables
contrast matrix used
PLS algorithm used
scaling used
validation method
model call
model terms
fitted model
a matrix of observations. NAs and Infs are not allowed.
a vector. NAs and Infs are not allowed.
the number of components to include in the model (see below).
additional arguments. Currently ignored.
Nelson Lee Afanador (nelson.afanador@mvdalab.com), Thanh Tran (thanh.tran@mvdalab.com)
This function should not be called directly, but through plsFit with the argument method="bidiagpls". It implements the Bidiag2 scores algorithm.
Indahl, Ulf G., (2014) The geometry of PLS1 explained properly: 10 key notes on mathematical properties of and some alternative algorithmic approaches to PLS1 modeling. Journal of Chemometrics, 28, 168:180.
Manne R., Analysis of two partial-least-squares algorithms for multi-variate calibration. Chemom. Intell. Lab. Syst. 1987; 2: 187:197.
plsFit