plsreg2 {plspm}R Documentation

PLS-R2: Partial Least Squares Regression 2

Description

Calculates partial least squares regression for the multivariate case (i.e. more than one response variable)

Usage

  plsreg2(X, Y, nc = 2)

Arguments

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)

Details

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.

Value

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.

Author(s)

Gaston Sanchez

References

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.

See Also

print.plsreg2, plot.plsreg2, plsreg1.

Examples

  ## 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)

[Package plspm version 0.1-4 Index]