Parameter Estimation in a Coupled System of Nonlinear Size-Structured Populations
A least squares technique is developed for identifying unknownparameters in a coupled system of nonlinear size-structuredpopulations. Convergence results for the parameter estimationtechnique are established. Ample numerical simulations andstatistical evidence are provided to demonstrate the feasibi...
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| Format: | Article |
| Language: | English |
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AIMS Press
2005-02-01
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| Series: | Mathematical Biosciences and Engineering |
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| Online Access: | https://www.aimspress.com/article/doi/10.3934/mbe.2005.2.289 |
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| author | Azmy S. Ackleh H.T. Banks Keng Deng Shuhua Hu |
| author_facet | Azmy S. Ackleh H.T. Banks Keng Deng Shuhua Hu |
| author_sort | Azmy S. Ackleh |
| collection | DOAJ |
| description | A least squares technique is developed for identifying unknownparameters in a coupled system of nonlinear size-structuredpopulations. Convergence results for the parameter estimationtechnique are established. Ample numerical simulations andstatistical evidence are provided to demonstrate the feasibilityof this approach. |
| format | Article |
| id | doaj-art-0bf4696757194dee89c9de382c024f1d |
| institution | Kabale University |
| issn | 1551-0018 |
| language | English |
| publishDate | 2005-02-01 |
| publisher | AIMS Press |
| record_format | Article |
| series | Mathematical Biosciences and Engineering |
| spelling | doaj-art-0bf4696757194dee89c9de382c024f1d2025-01-24T01:48:05ZengAIMS PressMathematical Biosciences and Engineering1551-00182005-02-012228931510.3934/mbe.2005.2.289Parameter Estimation in a Coupled System of Nonlinear Size-Structured PopulationsAzmy S. Ackleh0H.T. Banks1Keng Deng2Shuhua Hu3Department of Mathematics, University of Louisiana at Lafayette, Lafayette, Louisiana 70504-1010Center for Research in Scientific Computation, North Carolina State University, Raleigh, North Carolina 27695-8205Department of Mathematics, University of Louisiana at Lafayette, Lafayette, Louisiana 70504-1010Department of Mathematics, University of Louisiana at Lafayette, Lafayette, Louisiana 70504-1010A least squares technique is developed for identifying unknownparameters in a coupled system of nonlinear size-structuredpopulations. Convergence results for the parameter estimationtechnique are established. Ample numerical simulations andstatistical evidence are provided to demonstrate the feasibilityof this approach.https://www.aimspress.com/article/doi/10.3934/mbe.2005.2.289finite difference approximationcoupled system of nonlinear size-structuredpopulationsparameter estimationstandard deviation.numerical simulation |
| spellingShingle | Azmy S. Ackleh H.T. Banks Keng Deng Shuhua Hu Parameter Estimation in a Coupled System of Nonlinear Size-Structured Populations Mathematical Biosciences and Engineering finite difference approximation coupled system of nonlinear size-structuredpopulations parameter estimation standard deviation. numerical simulation |
| title | Parameter Estimation in a Coupled System of Nonlinear Size-Structured Populations |
| title_full | Parameter Estimation in a Coupled System of Nonlinear Size-Structured Populations |
| title_fullStr | Parameter Estimation in a Coupled System of Nonlinear Size-Structured Populations |
| title_full_unstemmed | Parameter Estimation in a Coupled System of Nonlinear Size-Structured Populations |
| title_short | Parameter Estimation in a Coupled System of Nonlinear Size-Structured Populations |
| title_sort | parameter estimation in a coupled system of nonlinear size structured populations |
| topic | finite difference approximation coupled system of nonlinear size-structuredpopulations parameter estimation standard deviation. numerical simulation |
| url | https://www.aimspress.com/article/doi/10.3934/mbe.2005.2.289 |
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