Model dispersion with PRISM; an alternative to MCMC for rapid analysis of models
| Autor: | Simon J. Mutch, Darren J. Croton, Manodeep Sinha, Alan R. Duffy, Ellert van der Velden |
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| Rok vydání: | 2019 |
| Předmět: |
Speedup
Calibration (statistics) Bayesian probability FOS: Physical sciences 01 natural sciences 03 medical and health sciences Bayes' theorem symbols.namesake 0103 physical sciences 010303 astronomy & astrophysics Instrumentation and Methods for Astrophysics (astro-ph.IM) 030304 developmental biology computer.programming_language Physics 0303 health sciences Probabilistic logic Astronomy and Astrophysics Markov chain Monte Carlo Python (programming language) Computational Physics (physics.comp-ph) Space and Planetary Science symbols Prism Astrophysics - Instrumentation and Methods for Astrophysics Algorithm computer Physics - Computational Physics |
| DOI: | 10.48550/arxiv.1901.08725 |
| Popis: | We have built PRISM, a "Probabilistic Regression Instrument for Simulating Models". PRISM uses the Bayes linear approach and history matching to construct an approximation ('emulator') of any given model, by combining limited model evaluations with advanced regression techniques, covariances and probability calculations. It is designed to easily facilitate and enhance existing Markov chain Monte Carlo (MCMC) methods by restricting plausible regions and exploring parameter space efficiently. However, PRISM can additionally be used as a standalone alternative to MCMC for model analysis, providing insight into the behavior of complex scientific models. With PRISM, the time spent on evaluating a model is minimized, providing developers with an advanced model analysis for a fraction of the time required by more traditional methods. This paper provides an overview of the different techniques and algorithms that are used within PRISM. We demonstrate the advantage of using the Bayes linear approach over a full Bayesian analysis when analyzing complex models. Our results show how much information can be captured by PRISM and how one can combine it with MCMC methods to significantly speed up calibration processes (>15 times faster). PRISM is an open-source Python package that is available under the BSD 3-Clause License (BSD-3) at https://github.com/1313e/PRISM and hosted at https://prism-tool.readthedocs.io. PRISM has also been reviewed by "The Journal of Open Source Software" (https://doi.org/10.21105/joss.01229). 28 pages, 13 figures, 1 table. Updated to reflect some changes made to published version |
| Databáze: | OpenAIRE |
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