A RAO-BLACKWELLIZED PARTICLE FILTER FOR JOINT PARAMETER ESTIMATION AND BIOMASS TRACKING IN A STOCHASTIC PREDATOR-PREY SYSTEM (Articolo in rivista)

Type
Label
  • A RAO-BLACKWELLIZED PARTICLE FILTER FOR JOINT PARAMETER ESTIMATION AND BIOMASS TRACKING IN A STOCHASTIC PREDATOR-PREY SYSTEM (Articolo in rivista) (literal)
Anno
  • 2014-01-01T00:00:00+01:00 (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#doi
  • 10.3934/mbe.2014.11.573 (literal)
Alternative label
  • Martin-Fernandez, Laura; Gilioli, Gianni; Lanzarone, Ettore; Miguez, Joaquin; Pasquali, Sara; Ruggeri, Fabrizio; Ruiz, Diego P. (2014)
    A RAO-BLACKWELLIZED PARTICLE FILTER FOR JOINT PARAMETER ESTIMATION AND BIOMASS TRACKING IN A STOCHASTIC PREDATOR-PREY SYSTEM
    in Mathematical biosciences and engineering; American Institute of Mathematical Sciences, Springfield [MO] (Stati Uniti d'America)
    (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#autori
  • Martin-Fernandez, Laura; Gilioli, Gianni; Lanzarone, Ettore; Miguez, Joaquin; Pasquali, Sara; Ruggeri, Fabrizio; Ruiz, Diego P. (literal)
Pagina inizio
  • 573 (literal)
Pagina fine
  • 597 (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#url
  • http://www.aimsciences.org/journals/displayArticlesnew.jsp?paperID=9557 (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#numeroVolume
  • 11 (literal)
Rivista
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#pagineTotali
  • 25 (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#numeroFascicolo
  • 3 (literal)
Note
  • ISI Web of Science (WOS) (literal)
  • Scopu (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#affiliazioni
  • University of Granada; University of Brescia; CNR IMATI; University of Carlos III Madrid; CNR IMATI; CNR IMATI; University of Granada (literal)
Titolo
  • A RAO-BLACKWELLIZED PARTICLE FILTER FOR JOINT PARAMETER ESTIMATION AND BIOMASS TRACKING IN A STOCHASTIC PREDATOR-PREY SYSTEM (literal)
Abstract
  • 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 response and (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. (literal)
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