Sobol4R0.4.0 package

Sobol Indices for Models with Fixed and Stochastic Parameters

autoplot

Autoplot implementations

bootstrap_indices

Bootstrap Sobol indices from stored samples

estimate_failure_probability

Estimate Failure Probability from Simulator Outputs

ishigami_model

Fast Ishigami Test Function

one_unit

Simulate one unit in the simple process

process_fun_indiv

Time to M successes for one individual

process_fun_mean_to_M

QoI wrapper for the process model

process_fun_row_wise

Process model for a matrix of individuals

sobol_design

Create Sobol Sampling Designs

sobol_example_covariate_large

Example 3: Large covariate dependent random effect

sobol_example_covariate_small

Example 4: Slight covariate dependent random effect

sobol_example_g_deterministic

Example 1: Deterministic G-function (reference case)

sobol_example_process

Example 5: Sobol indices for the process model

sobol_example_random_output

Example 2: Random effect on the output (constant Gaussian noise)

sobol_g_function

Sobol G-function (Saltelli reference function) - C++ backend

sobol_g_R

Sobol G-function (Saltelli reference function)

sobol_g2_additive_noise_R

Additive Gaussian noise on the Sobol G-function (k = 2)

sobol_g2_additive_noise

Additive Gaussian noise on the Sobol G-function (k = 2) - C++ backend

sobol_g2_function

Sobol G-function restricted to the first two inputs - C++ backend

sobol_g2_qoi_covariate_mean_R

Quantity-of-interest wrapper for the covariate noisy G-function (k = 2...

sobol_g2_qoi_covariate_mean

QoI wrapper for covariate noisy G-function (k = 2) - C++ backend

sobol_g2_qoi_mean_R

Quantity-of-interest wrapper for the noisy G-function (k = 2)

sobol_g2_qoi_mean

QoI wrapper for the noisy G-function (k = 2) - C++ backend

sobol_g2_R

Sobol G-function restricted to the first two inputs

sobol_g2_with_covariate_noise_R

Additive Gaussian noise on the Sobol G-function (k = 2)

sobol_g2_with_covariate_noise

Covariate dependent Gaussian noise on the Sobol G-function (k = 2) - C...

sobol_indices

Sobol Indices for Stochastic Simulators

sobol_reliability

Reliability-Oriented Sobol Indices

sobol4r_clinic_model

Two-step clinic model wrapper for Sobol designs

sobol4r_design

Design generation for Sobol indices

sobol4r_mm1_model

M/M/1 queue model wrapper for Sobol designs

sobol4r_qoi_indices

Generic QoI-based Sobol indices for a stochastic model

sobol4r_run

Run Sobol analysis with optional QoI wrapper

Sobol4R-package

Sobol4R-package

summarise_sobol

Summarise Sobol Indices

Tools to design experiments, compute Sobol sensitivity indices, and summarise stochastic responses inspired by the strategy described by Zhu and Sudret (2021) <doi:10.1016/j.ress.2021.107815>. Includes helpers to optimise toy models implemented in C++, visualise indices with uncertainty quantification, and derive reliability-oriented sensitivity measures based on failure probabilities. It is further detailed in Logosha, Maumy and Bertrand (2022) <doi:10.1063/5.0246026> and (2023) <doi:10.1063/5.0246024> or in Bertrand, Logosha and Maumy (2024) <https://hal.science/hal-05371803>, <https://hal.science/hal-05371795> and <https://hal.science/hal-05371798>.

  • Maintainer: Frederic Bertrand
  • License: GPL-3
  • Last published: 2025-12-02