fast99
(Package: sensitivity) :
Extended Fourier Amplitude Sensitivity Test
fast99 implements the so-called "extended-FAST" method (Saltelli et al. 1999). This method allows the estimation of first order and total Sobol' indices for all the factors (alltogether 2p indices, where p is the number of factors) at a total cost of n * p simulations.
sensiHSIC
(Package: sensitivity) :
Sensitivity Indices based on Hilbert-Schmidt Independence Criterion (HSIC)
sensiHSIC conducts a sensitivity analysis where the impact of an input variable is defined in terms of the distance between the input/output joint probability distribution and the product of their marginals when they are embedded in a Reproducing Kernel Hilbert Space (RKHS). This distance corresponds to the Hilbert-Schmidt Independence Criterion (HSIC) proposed by Gretton et al. (2005) and serves as a dependence measure between random variables, see Da Veiga (2014) for an illustration in the context of sensitivity analysis.
sobolmartinez
(Package: sensitivity) :
Monte Carlo Estimation of Sobol' Indices (formulas of Martinez (2011))
sobolmartinez implements the Monte Carlo estimation of the Sobol' indices for both first-order and total indices using correlation coefficients-based formulas, at a total cost of (p + 2) * n model evaluations. These are called the Martinez estimators.
sensiFdiv
(Package: sensitivity) :
Sensitivity Indices based on Csiszar f-divergence
sensiFdiv conducts a density-based sensitivity analysis where the impact of an input variable is defined in terms of dissimilarity between the original output density function and the output density function when the input variable is fixed. The dissimilarity between density functions is measured with Csiszar f-divergences. Estimation is performed through kernel density estimation and the function kde of the package ks.
sobolowen
(Package: sensitivity) :
Monte Carlo Estimation of Sobol' Indices (improved formulas of Owen (2013)
sobolowen implements the Monte Carlo estimation of the Sobol' indices for both first-order and total indices at the same time (alltogether 2p indices). Take as input 3 independent matrices. These are called the Owen estimators.
template.replace replaces keys within special markups with values in a so-called template file. Pieces of R code can be put into the markups of the template file, and are evaluated during the replacement.
sobolroalhs
(Package: sensitivity) :
Sobol' Indices Estimation Using Replicated OA-based LHS
sobolroalhs implements the estimation of the Sobol' sensitivity indices introduced by Tissot & Prieur (2012) using two Orthogonal Array-based Latin Hypercubes. This function allows the estimation of all first-order indices or all closed second-order indices (containing the sum of the second-order effect between two inputs and the individual effects of each input) at a total cost of 2*N. For closed second-order indices N=q^2 where q >= d-1 is a prime number denoting the number of levels of the orthogonal array, and where d is the number of factors.
sobol2002
(Package: sensitivity) :
Monte Carlo Estimation of Sobol' Indices (scheme by Saltelli 2002)
sobol2002 implements the Monte Carlo estimation of the Sobol' indices for both first-order and total indices at the same time (alltogether 2p indices), at a total cost of (p + 2) * n model evaluations. These are called the Saltelli estimators.
Perform a kriging-based global sensitivity analysis taking into account both the meta-model and the Monte-Carlo errors. The Sobol indices are estimated with a Monte-Carlo integration and the true function is substituted by a kriging model. It is built thanks to the function km of the package DiceKriging. The complete conditional predictive distribution of the kriging model is considered (not only the predictive mean).
providing 
.