o2pls {o2plsda} | R Documentation |
fit O2PLS model with best nc, nx, ny
Description
fit O2PLS model with best nc, nx, ny
Usage
o2pls(X, Y, nc, nx, ny, scale = FALSE, center = FALSE)
Arguments
X |
a Numeric matrix (input) |
Y |
a Numeric matrix (input) |
nc |
Integer. Number of joint PLS components. |
nx |
Integer. Number of orthogonal components in X |
ny |
Integer. Number of orthogonal components in Y |
scale |
boolean values determining if data should be scaled or not |
center |
boolean values determining if data should be centered or not |
Value
An object containing
Xscore |
Joint |
Xloading |
Joint |
Yscore |
Joint |
Yloading |
Joint |
TYosc |
Orthogonal |
PYosc |
Orthogonal |
WYosc |
Orthogonal |
UXosc |
Orthogonal |
PXosc |
Orthogonal |
CXosc |
Orthogonal |
BU |
Regression coefficient in |
BT |
Regression coefficient in |
Xhat |
Prediction of |
Yhat |
Prediction of |
R2Xhat |
Variation of the predicted |
R2Yhat |
Variation of the predicted |
R2X |
Variation of the modeled part in |
R2Y |
Variation of the modeled part in |
R2Xcorr |
Variation of the joint part in |
R2Ycorr |
Variation of the joint part in |
R2Xo |
Variation of the orthogonal part in |
R2Yo |
Variation of the orthogonal part in |
R2Xp |
Variation in |
R2Yp |
Variation in |
varXj |
Variation in each Latent Variable (LV) in |
varYj |
Variation in each Latent Variable (LV) in |
varXorth |
Variation in each Latent Variable (LV) in |
varYorth |
Variation in each Latent Variable (LV) in |
Exy |
Residuals in |
Fxy |
Residuals in |
Author(s)
Kai Guo
Examples
set.seed(123)
X = matrix(rnorm(500),50,10)
Y = matrix(rnorm(500),50,10)
X = scale(X, scale = TRUE)
Y = scale(Y, scale = TRUE)
fit <- o2pls(X, Y, 1, 2, 2)
summary(fit)