sobol_example_covariate_large

Third input C3 is uniform on [1, 100], used as the mean of a Gaussian
noise term added to the G-function. Quantity of interest is the mean
of repeated evaluations.

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>.

Frederic Bertrand

Sobol4R

Sobol Indices for Models with Fixed and Stochastic Parameters

Elizaveta Logosha

Myriam Maumy-Bertrand

sobol_example_covariate_large function

<dl><dt>n</dt>
<dd>Monte Carlo sample size for each base design.</dd>
<dt>nrep_qoi</dt>
<dd>Number of repetitions for the QoI.</dd>
<dt>order</dt>
<dd>Maximum interaction order.</dd>
<dt>nboot</dt>
<dd>Number of bootstrap replicates.</dd></dl>

Arguments

Example 3: Large covariate dependent random effect — sobol_example_covariate_large

<dl>

<dt>n</dt>
<dd>Monte Carlo sample size for each base design.</dd>


<dt>nrep_qoi</dt>
<dd>Number of repetitions for the QoI.</dd>


<dt>order</dt>
<dd>Maximum interaction order.</dd>


<dt>nboot</dt>
<dd>Number of bootstrap replicates.</dd>

</dl>

sobol_example_covariate_large: Example 3: Large covariate dependent random effect

Description

Usage

Value

Arguments