A Rao-Blackwellized particle filter for joint parameter estimation and biomass tracking in a stochastic predator-prey system
Functional response estimation and population tracking in predator-prey systems are critical problems in ecology. In this paper we consider a stochastic predator-prey system with a Lotka-Volterra functional response and propose a particle filtering method for: (a) estimating the behavioral parameter...
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| Format: | Article |
| Language: | English |
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AIMS Press
2013-12-01
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| Series: | Mathematical Biosciences and Engineering |
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| Online Access: | https://www.aimspress.com/article/doi/10.3934/mbe.2014.11.573 |
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| author | Laura Martín-Fernández Gianni Gilioli Ettore Lanzarone Joaquín Míguez Sara Pasquali Fabrizio Ruggeri Diego P. Ruiz |
| author_facet | Laura Martín-Fernández Gianni Gilioli Ettore Lanzarone Joaquín Míguez Sara Pasquali Fabrizio Ruggeri Diego P. Ruiz |
| author_sort | Laura Martín-Fernández |
| collection | DOAJ |
| description | Functional response estimation and population tracking in predator-prey systems are critical problems in ecology. In this paper we consider a stochastic predator-prey system with a Lotka-Volterra functional response and propose a particle filtering method for: (a) estimating the behavioral parameter representing the rate of effective search per predator in the functional responseand (b) forecasting the population biomass using field data. In particular, the proposed technique combines a sequential Monte Carlo sampling scheme for tracking the time-varying biomass with the analytical integration of the unknown behavioral parameter. In order to assess the performance of the method, we show results for both synthetic and observed data collected in an acarine predator-prey system, namely the pest mite Tetranychus urticae and the predatory mite Phytoseiulus persimilis. |
| format | Article |
| id | doaj-art-7c5a9c6172c44a4eb2fb18d9d4068cc7 |
| institution | Kabale University |
| issn | 1551-0018 |
| language | English |
| publishDate | 2013-12-01 |
| publisher | AIMS Press |
| record_format | Article |
| series | Mathematical Biosciences and Engineering |
| spelling | doaj-art-7c5a9c6172c44a4eb2fb18d9d4068cc72025-01-24T02:28:12ZengAIMS PressMathematical Biosciences and Engineering1551-00182013-12-0111357359710.3934/mbe.2014.11.573A Rao-Blackwellized particle filter for joint parameter estimation and biomass tracking in a stochastic predator-prey systemLaura Martín-Fernández0Gianni Gilioli1Ettore Lanzarone2Joaquín Míguez3Sara Pasquali4Fabrizio Ruggeri5Diego P. Ruiz6Departamento de Física Aplicada, Universidad de Granada, Avda. Fuentenueva s/n, 18071 GranadaDepartment of Molecular and Translational Medicine, University of Brescia, Viale Europa 11, 25125 BresciaCNR-IMATI, Via Bassini 15, 20133 MilanoDepartamento de Teoría de la Señal y Comunicaciones, Universidad Carlos III de Madrid, Avda. de la Universidad 30, 28911 Leganés, MadridCNR-IMATI, Via Bassini 15, 20133 MilanoCNR-IMATI, Via Bassini 15, 20133 MilanoDepartamento de Física Aplicada, Universidad de Granada, Avda. Fuentenueva s/n, 18071 GranadaFunctional response estimation and population tracking in predator-prey systems are critical problems in ecology. In this paper we consider a stochastic predator-prey system with a Lotka-Volterra functional response and propose a particle filtering method for: (a) estimating the behavioral parameter representing the rate of effective search per predator in the functional responseand (b) forecasting the population biomass using field data. In particular, the proposed technique combines a sequential Monte Carlo sampling scheme for tracking the time-varying biomass with the analytical integration of the unknown behavioral parameter. In order to assess the performance of the method, we show results for both synthetic and observed data collected in an acarine predator-prey system, namely the pest mite Tetranychus urticae and the predatory mite Phytoseiulus persimilis.https://www.aimspress.com/article/doi/10.3934/mbe.2014.11.573state-space modelprey-predator systemparameter estimationrao-blackwellized particle filter.population tracking |
| spellingShingle | Laura Martín-Fernández Gianni Gilioli Ettore Lanzarone Joaquín Míguez Sara Pasquali Fabrizio Ruggeri Diego P. Ruiz A Rao-Blackwellized particle filter for joint parameter estimation and biomass tracking in a stochastic predator-prey system Mathematical Biosciences and Engineering state-space model prey-predator system parameter estimation rao-blackwellized particle filter. population tracking |
| title | A Rao-Blackwellized particle filter for joint parameter estimation and biomass tracking in a stochastic predator-prey system |
| title_full | A Rao-Blackwellized particle filter for joint parameter estimation and biomass tracking in a stochastic predator-prey system |
| title_fullStr | A Rao-Blackwellized particle filter for joint parameter estimation and biomass tracking in a stochastic predator-prey system |
| title_full_unstemmed | A Rao-Blackwellized particle filter for joint parameter estimation and biomass tracking in a stochastic predator-prey system |
| title_short | A Rao-Blackwellized particle filter for joint parameter estimation and biomass tracking in a stochastic predator-prey system |
| title_sort | rao blackwellized particle filter for joint parameter estimation and biomass tracking in a stochastic predator prey system |
| topic | state-space model prey-predator system parameter estimation rao-blackwellized particle filter. population tracking |
| url | https://www.aimspress.com/article/doi/10.3934/mbe.2014.11.573 |
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