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>.

Algorithm to estimate the Sobol indices using a non-parametric fit of the regression curve. The bandwidth is estimated using bootstrap to reduce the finite-sample bias. The package is based on the paper Solís, M. (2018) <arXiv:1803.03333>.

Functions for evaluating tournament predictions, simulating results from individual soccer matches and tournaments. See <http://sandsynligvis.dk/2018/08/03/world-cup-prediction-winners/> for more information.

A set of functions to quantify and visualise 
    social autocorrelation.

Tools for constructing, auditing, and visualizing temporal
    social interaction networks from event-log data. Supports graph
    construction from raw user-to-user interaction logs, longitudinal
    tracking of network structure, community dynamics, user role
    trajectories, and concentration of engagement over time. Designed
    for computational social science, platform analytics, and digital
    community health monitoring. Includes four longitudinal audit indices: the
    Network Drift Index ('NDI'), Community Fragmentation Index ('CFI'),
    Visibility Concentration Index ('VCI'), and Role Mobility Index ('RMI').
    'NDI', 'CFI', 'VCI', and 'RMI' are purpose-built composite scores for longitudinal platform auditing.

Compute Average Attributable Fraction (AAF) and produce a GT table with Odds.ratio, Average Marginal Effects and AAF, with confidence interval and p.value. Also compute other metrics such as Yule's Q and Cramer's V. For more details, see Fergusion and al. (2024) <doi:10.1007/s10654-024-01129-1>.