plsreg2 {plspm} | R Documentation |
Calculates partial least squares regression for the multivariate case (i.e. more than one response variable)
plsreg2(X, Y, nc = 2)
X |
A numeric matrix or data frame containing the predictor variables. |
Y |
A numeric matrix or data frame containing the predictand variables. |
nc |
The number of extracted PLS components (2 by default) |
The minimum number of PLS components nc
is 2.
The data is scaled to standardized values (mean=0, variance=1).
No missing data are allowed.
Argument Y
must contain more than one variable. If Y
is a vector, you may use the function plsreg1
.
An object of class "plsreg2"
, basically a list with the following elements:
x.scores |
components of the predictor variables. |
x.loads |
loadings of the predictor variables. |
y.scores |
components of the predictand variables. |
y.loads |
loadings of the predictand variables. |
raw.wgs |
weights to calculate the PLS scores with the deflated matrices of predictor variables. |
mod.wgs |
modified weights to calculate the PLS scores with the matrix of predictor variables. |
cor.tx |
modified weights to calculate the PLS scores with the matrix of predictor variables. |
cor.ty |
modified weights to calculate the PLS scores with the matrix of predictor variables. |
std.coef |
Vector of standardized regression coefficients. |
coeffs |
Vector of regression coefficients (used with the original data scale). |
y.pred |
Vector of predicted values. |
resid |
Vector of residuals. |
expvar |
table with R-squared coefficients. |
Q2 |
table of Q2 indexes (i.e. leave-one-out cross validation). |
Q2cum |
table of cummulated Q2 indexes. |
VIP |
Variable Importance for Projection. |
Gaston Sanchez
Geladi, P., and Kowlaski, B. (1986) Partial Least Squares Regression: A Tutorial. Analytica Chimica Acta, 185, pp. 1-17.
Hoskuldsson, A. (1988) PLS Regression Methods. Journal of Chemometrics, 2, pp. 211-228.
Tenenhaus, M. (1998) La Regression PLS. Theorie et Pratique. Editions TECHNIP, Paris.
Valencia, J.L., Diaz-Llanos, F.J. (2004) Metodos de Prediccion en Situaciones Limite. Editorial La Muralla, S.A. Madrid.
print.plsreg2
, plot.plsreg2
, plsreg1
.
## Not run: ## example of PLSR2 with the vehicles dataset data(vehicles) pls2 <- plsreg2(vehicles[,1:12], vehicles[,13:16]) pls2 plot(pls2) ## End(Not run)