PLSPCE-class: Class '"PLSPCE"'
In plspolychaos: Sensitivity Indexes from Polynomial Chaos Expansions and PLS

Description Slots Methods Note See Also

An S4 class container for the result of the function calcPLSPCE.

indexes:

matrix with as many rows as inputs and three columns. Values of the PLS-PCE sensitivity indexes. The column labels are LE, PE, TPE.

indexes[i, "LE"] is the Linear Effect of the input i.
indexes[i, "PE"] is the Polynomial Effect. It is the effect of the monomials in which only the input i appears.
indexes[i, "TPE"] is the Total Polynomial Effect. It is the effect of all the monomials in which the input i appears.

indexes.percent:

matrix. Percentages of the PLS-PCE sensitivity indexes, i.e values of indexes expressed as percentages of the sums of their columns.

ncopt:

number of the optimal component.

R2:

matrix with as many rows as components and three columns. The columns are labeled R2, %R2 and %R2cum. They store respectively the R2 values, percentages of their column sums, and cumulated values of their percentages.

Q2:

matrix with as many rows as components and two columns. The columns are labeled Q2 and Q2cum. They store respectively the Q2 and the Q2cum values.

rmsep:

matrix with as many rows as components and one column. Root mean square error predictions.

COEF:

matrix with as many rows as monomials plus one and as many columns as components. PLS-regression coefficients. The first row is the constant term.

betaCR:

matrix with as many rows as monomials and as many columns as components. The centered-reducted PLS-regression coefficients, for all the components.

y.hat:

vector of length equal to the number of rows of the dataset. Metamodel outputs.

STRUC:

object of class PCEdesign coding the polynomial structure.

print: signature(x = "PLSPCE", all=FALSE, ...): method of function print. When option all is FALSE, some slots are hidden : RMSEP, coef, betaCR, y.hat, STRUC. When option all is set to TRUE, the names of the hidden slots are printed. The additional arguments are passed to the print.default function.
show: signature(object = "PLSPCE"): same as function print, without any arguments.
plot: signature(x = "PLSPCE", pce, options =c("fit", "bar", "compo")): method of function plot. Different plots are drawn, according to options. When it includes “fit”, computer model outputs against metamodel outputs. When it includes “bar”, barplots of the polynomial and total polynomial effects (PE and TPE). When it includes “compo”, TPE against components. This last plot requires the calculation of the TPE for each component, which may take some time.