gsaot: an R package for Optimal Transport-based sensitivity analysis

TL;DR

gsaot is an R package that enables model-agnostic global sensitivity analysis using Optimal Transport methods, offering easy-to-use estimation and visualization tools for researchers.

Contribution

This paper introduces gsaot, a new R package that implements state-of-the-art Optimal Transport algorithms for sensitivity analysis, with a focus on usability and visualization.

Findings

Provides a comprehensive overview of the theoretical foundations.

Demonstrates the package's application in various examples.

Shows effectiveness of Optimal Transport methods in sensitivity analysis.

Abstract

gsaot is an R package for Optimal Transport-based global sensitivity analysis. It provides a simple interface for indices estimation using a variety of state-of-the-art Optimal Transport solvers such as the network simplex and Sinkhorn-Knopp. The package is model-agnostic, allowing analysts to perform the sensitivity analysis as a post-processing step. Moreover, gsaot provides functions for indices and statistics visualization. In this work, we provide an overview of the theoretical grounds, of the implemented algorithms, and show how to use the package in different examples.