Computation of sensitivity indexes by using a method based on a truncated Polynomial Chaos Expansion of the response and regression PLS, for computer models with correlated continuous inputs, whatever the input distribution. The truncated Polynomial Chaos Expansion is built from the multivariate Legendre orthogonal polynomials. The number of runs (rows) can be smaller than the number of monomials. It is possible to select only the most significant monomials. Of course, this package can also be used if the inputs are independent. Note that, when they are independent and uniformly distributed, the package 'polychaosbasics' is more appropriate.
|Author||A. Bouvier [aut], J.-P. Gauchi [cre], A. Bensadoun [ctb]|
|Date of publication||2016-05-09 21:37:50|
|Maintainer||Annie Bouvier <firstname.lastname@example.org>|
|License||GPL (>= 2)|
analyticsPolyLeg: Simulate a Dataset and Calculate Legendre Polynomials
calcPLSPCE: Compute PLS-PCE Sensitivity Indexes
descrdata: Main Characteristics of the Dataset
getNames: Display Structure of a Class
PCEdesign-class: Class '"PCEdesign"'
PCEpoly-class: Class '"PCEpoly"'
PLSPCE-class: Class '"PLSPCE"'
plspolychaos-package: Sensitivity Indexes from Polynomial Chaos Expansions and PLS
polyLeg: Calculate Legendre Polynomials on a Dataset