Simulations in statistical workflows

Philosophical Transactions of the Royal Society A Mathematical Physical and Engineering Sciences 2026 Open access

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Authors: Paul‐Christian Bürkner, Marvin Schmitt, Stefan T. Radev
DOI: 10.1098/rsta.2024.0616
Cited by: 1
References: 122

Abstract

Simulations play important and diverse roles in statistical workflows, for example, in model specification, checking, validation and even directly in model inference. Over the past decades, the application areas and overall potential of simulations in statistical workflows have expanded significantly, driven by the development of new simulation-based algorithms and exponentially increasing computational resources. In this paper, we examine past and current trends in the field and offer perspectives on how simulations may shape the future of statistical practice. This article is part of the theme issue 'Statistical workflow'.

Fields of Study & Subjects

Scientific Computing and Data Management Adversarial Robustness in Machine Learning Data Analysis with R

Publication details

Journal / source
Philosophical Transactions of the Royal Society A Mathematical Physical and Engineering Sciences
Publisher
The Royal Society
Volume
384
Issue
2321
Publication date
21 May 2026
Language
EN