process_fun_mean_to_M

For each row of <code>X</code>, evaluates <code>process_fun_row_wise</code> several times
and returns the mean time to M successes.

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

process_fun_mean_to_M function

<dl><dt>X</dt>
<dd>Matrix or data.frame of parameters.</dd>
<dt>M</dt>
<dd>Target number of successes.</dd>
<dt>nrep</dt>
<dd>Number of repetitions for the QoI.</dd></dl>

Arguments

QoI wrapper for the process model — process_fun_mean_to_M

<dl>

<dt>X</dt>
<dd>Matrix or data.frame of parameters.</dd>


<dt>M</dt>
<dd>Target number of successes.</dd>


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

</dl>

process_fun_mean_to_M: QoI wrapper for the process model

Description

Usage

Value

Arguments