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Updated: May 29, 2026
11:39
A Quantitative Fitness Analysis Workflow
Published on: August 13, 2012
Simulations in statistical workflows
Paul-Christian Bürkner1, Marvin Schmitt2, Stefan T Radev3
1Department of Statistics, TU Dortmund, Dortmund, North Rhine-Westphalia, Germany.
Summary
Simulations are crucial for statistical workflows, enhancing model checking, validation, and inference. Advances in algorithms and computing power are expanding their use and future potential in statistics.
Area of Science:
- Statistics
- Computational Statistics
Background:
- Simulations are integral to statistical workflows, aiding in model specification, checking, validation, and inference.
- The scope and impact of simulations in statistics have grown substantially due to algorithmic advancements and increased computational power.
Purpose of the Study:
- To review historical and current trends in the use of simulations in statistical workflows.
- To provide insights into the future role of simulations in statistical practice.
Main Methods:
- Literature review of simulation-based algorithms and their applications.
- Analysis of computational resource growth and its impact on statistical methods.
Main Results:
- Significant expansion in the application areas and potential of simulations over recent decades.
- Identification of key drivers for this expansion, including new algorithms and computational resources.
Conclusions:
- Simulations are increasingly vital for robust statistical analysis and inference.
- Future statistical practice will likely be further shaped by sophisticated simulation techniques and enhanced computational capabilities.
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