A comparison of computational efficiencies of stochastic algorithms in terms of two infection models
In this paper, we investigate three particular algorithms: a stochastic simulation algorithm (SSA), and explicit and implicit tau-leaping algorithms. To compare these methods, we used them to analyze two infection models: a Vancomycin-resistant enterococcus (VRE) infection model at the population l...
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| Format: | Article |
| Language: | English |
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AIMS Press
2012-06-01
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| Series: | Mathematical Biosciences and Engineering |
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| Online Access: | https://www.aimspress.com/article/doi/10.3934/mbe.2012.9.487 |
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| author | H. Thomas Banks Shuhua Hu Michele Joyner Anna Broido Brandi Canter Kaitlyn Gayvert Kathryn Link |
| author_facet | H. Thomas Banks Shuhua Hu Michele Joyner Anna Broido Brandi Canter Kaitlyn Gayvert Kathryn Link |
| author_sort | H. Thomas Banks |
| collection | DOAJ |
| description | In this paper, we investigate three particular algorithms: a stochastic simulation algorithm (SSA), and explicit and implicit tau-leaping algorithms. To compare these methods, we used them to analyze two infection models: a Vancomycin-resistant enterococcus (VRE) infection model at the population level, and a Human Immunodeficiency Virus (HIV) within host infection model. While the first has a low species count and few transitions, the second is more complex with a comparable number of species involved. The relative efficiency of each algorithm is determined based on computational time and degree of precision required. The numerical results suggest that all three algorithms have the similar computational efficiency for the simpler VRE model, and the SSA is the best choice due to its simplicity and accuracy. In addition, we have found that with the larger and more complex HIV model, implementation and modification of tau-Leaping methods are preferred. |
| format | Article |
| id | doaj-art-3f8a8954aaec4e6da9d8b3fc2dd3235c |
| institution | Kabale University |
| issn | 1551-0018 |
| language | English |
| publishDate | 2012-06-01 |
| publisher | AIMS Press |
| record_format | Article |
| series | Mathematical Biosciences and Engineering |
| spelling | doaj-art-3f8a8954aaec4e6da9d8b3fc2dd3235c2025-01-24T02:07:00ZengAIMS PressMathematical Biosciences and Engineering1551-00182012-06-019348752610.3934/mbe.2012.9.487A comparison of computational efficiencies of stochastic algorithms in terms of two infection modelsH. Thomas Banks0Shuhua Hu1Michele Joyner2Anna Broido3Brandi Canter4Kaitlyn Gayvert5Kathryn Link6Center for Research in Scientific Computation, Center for Quantitative Sciences in Biomedicine, North Carolina State University, Raleigh, NC 27695-8212Center for Research in Scientific Computation, Center for Quantitative Sciences in Biomedicine, North Carolina State University, Raleigh, NC 27695-8212Center for Research in Scientific Computation, Center for Quantitative Sciences in Biomedicine, North Carolina State University, Raleigh, NC 27695-8212Center for Research in Scientific Computation, Center for Quantitative Sciences in Biomedicine, North Carolina State University, Raleigh, NC 27695-8212Center for Research in Scientific Computation, Center for Quantitative Sciences in Biomedicine, North Carolina State University, Raleigh, NC 27695-8212Center for Research in Scientific Computation, Center for Quantitative Sciences in Biomedicine, North Carolina State University, Raleigh, NC 27695-8212Center for Research in Scientific Computation, Center for Quantitative Sciences in Biomedicine, North Carolina State University, Raleigh, NC 27695-8212In this paper, we investigate three particular algorithms: a stochastic simulation algorithm (SSA), and explicit and implicit tau-leaping algorithms. To compare these methods, we used them to analyze two infection models: a Vancomycin-resistant enterococcus (VRE) infection model at the population level, and a Human Immunodeficiency Virus (HIV) within host infection model. While the first has a low species count and few transitions, the second is more complex with a comparable number of species involved. The relative efficiency of each algorithm is determined based on computational time and degree of precision required. The numerical results suggest that all three algorithms have the similar computational efficiency for the simpler VRE model, and the SSA is the best choice due to its simplicity and accuracy. In addition, we have found that with the larger and more complex HIV model, implementation and modification of tau-Leaping methods are preferred.https://www.aimspress.com/article/doi/10.3934/mbe.2012.9.487continuous time markov chain modelsgillespietau-leapingdynamical modelsstochastic simulation algorithmsbacterial and viral infection models. |
| spellingShingle | H. Thomas Banks Shuhua Hu Michele Joyner Anna Broido Brandi Canter Kaitlyn Gayvert Kathryn Link A comparison of computational efficiencies of stochastic algorithms in terms of two infection models Mathematical Biosciences and Engineering continuous time markov chain models gillespie tau-leaping dynamical models stochastic simulation algorithms bacterial and viral infection models. |
| title | A comparison of computational efficiencies of stochastic algorithms in terms of two infection models |
| title_full | A comparison of computational efficiencies of stochastic algorithms in terms of two infection models |
| title_fullStr | A comparison of computational efficiencies of stochastic algorithms in terms of two infection models |
| title_full_unstemmed | A comparison of computational efficiencies of stochastic algorithms in terms of two infection models |
| title_short | A comparison of computational efficiencies of stochastic algorithms in terms of two infection models |
| title_sort | comparison of computational efficiencies of stochastic algorithms in terms of two infection models |
| topic | continuous time markov chain models gillespie tau-leaping dynamical models stochastic simulation algorithms bacterial and viral infection models. |
| url | https://www.aimspress.com/article/doi/10.3934/mbe.2012.9.487 |
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