Marathon: An Open Source Software Library for the Analysis of Markov-Chain Monte Carlo Algorithms
محفوظ في:
| الحاوية / القاعدة: | PLoS One vol. 11, no. 1 (Jan 2016), p. e0147935 |
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| المؤلف الرئيسي: | |
| مؤلفون آخرون: | |
| منشور في: |
Public Library of Science
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| الموضوعات: | |
| الوصول للمادة أونلاين: | Citation/Abstract Full Text Full Text - PDF |
| الوسوم: |
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MARC
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| 022 | |a 1932-6203 | ||
| 024 | 7 | |a 10.1371/journal.pone.0147935 |2 doi | |
| 035 | |a 1761243182 | ||
| 045 | 2 | |b d20160101 |b d20160131 | |
| 084 | |a 174835 |2 nlm | ||
| 100 | 1 | |a Rechner, Steffen | |
| 245 | 1 | |a Marathon: An Open Source Software Library for the Analysis of Markov-Chain Monte Carlo Algorithms | |
| 260 | |b Public Library of Science |c Jan 2016 | ||
| 513 | |a Journal Article | ||
| 520 | 3 | |a We present the software library marathon, which is designed to support the analysis of sampling algorithms that are based on the Markov-Chain Monte Carlo principle. The main application of this library is the computation of properties of so-called state graphs, which represent the structure of Markov chains. We demonstrate applications and the usefulness of marathon by investigating the quality of several bounding methods on four well-known Markov chains for sampling perfect matchings and bipartite graphs. In a set of experiments, we compute the total mixing time and several of its bounds for a large number of input instances. We find that the upper bound gained by the famous canonical path method is often several magnitudes larger than the total mixing time and deteriorates with growing input size. In contrast, the spectral bound is found to be a precise approximation of the total mixing time. | |
| 610 | 4 | |a American Mathematical Society | |
| 651 | 4 | |a United States--US | |
| 651 | 4 | |a Germany | |
| 653 | |a Monte Carlo simulation | ||
| 653 | |a Computer programs | ||
| 653 | |a Applied mathematics | ||
| 653 | |a Graphs | ||
| 653 | |a Markov chains | ||
| 653 | |a Computer science | ||
| 653 | |a Upper bounds | ||
| 653 | |a Algorithms | ||
| 653 | |a Open source software | ||
| 653 | |a Economic | ||
| 653 | |a Methods | ||
| 653 | |a Sampling | ||
| 653 | |a Libraries | ||
| 653 | |a Probability distribution | ||
| 653 | |a Computer simulation | ||
| 653 | |a Markov analysis | ||
| 653 | |a Software | ||
| 700 | 1 | |a Berger, Annabell | |
| 773 | 0 | |t PLoS One |g vol. 11, no. 1 (Jan 2016), p. e0147935 | |
| 786 | 0 | |d ProQuest |t Health & Medical Collection | |
| 856 | 4 | 1 | |3 Citation/Abstract |u https://www.proquest.com/docview/1761243182/abstract/embedded/6A8EOT78XXH2IG52?source=fedsrch |
| 856 | 4 | 0 | |3 Full Text |u https://www.proquest.com/docview/1761243182/fulltext/embedded/6A8EOT78XXH2IG52?source=fedsrch |
| 856 | 4 | 0 | |3 Full Text - PDF |u https://www.proquest.com/docview/1761243182/fulltextPDF/embedded/6A8EOT78XXH2IG52?source=fedsrch |