Bayesian inference for functional response in a stochastic predator-prey system (Articolo in rivista)

Type

• Articolo in rivista (Classe)
• Prodotto della ricerca (Classe)

Label

• Bayesian inference for functional response in a stochastic predator-prey system (Articolo in rivista) (literal)

Anno

• 2008-01-01T00:00:00+01:00 (literal)

Alternative label

• Gilioli G.; Pasquali S; Ruggeri F. (2008)
  Bayesian inference for functional response in a stochastic predator-prey system
  in Bulletin of mathematical biology (Print)
  (literal)

Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#autori

• Gilioli G.; Pasquali S; Ruggeri F. (literal)

Pagina inizio

• 358 (literal)

Pagina fine

• 381 (literal)

Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#numeroVolume

• 70 (literal)

Rivista

• Bulletin of mathematical biology (Rivista)

Note

• ISI Web of Science (WOS) (literal)
• Scopu (literal)

Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#affiliazioni

• Gilioli G., Dipartimento GESAF, Università di Reggio Calabria, 89061 Gallina di Reggio Calabria, Italy - Pasquali S., CNR-IMATI, Via Bassini 15, 20133 Milano, Italy - Ruggeri F., CNR-IMATI, Via Bassini 15, 20133 Milano, Italy (literal)

Titolo

• Bayesian inference for functional response in a stochastic predator-prey system (literal)

Abstract

• We present a Bayesian method for functional response parameter estimation starting from time series of field data on predator-prey dynamics. Population dynamics is described by a system of stochastic differential equations in which behavioral stochasticities are represented by noise terms affecting each population as well as their interaction. We focus on the estimation of a behavioral parameter appearing in the functional response of predator to prey abundance when a small number of observations is available. To deal with small sample sizes, latent data are introduced between each pair of field observations and are considered as missing data. The method is applied to both simulated and observational data. The results obtained using different numbers of latent data are compared with those achieved following a frequentist approach. As a case study, we consider an acarine predator-prey system relevant to biological control problems. (literal)

Prodotto di

• Modellizzazione di sistemi stocastici (ICT.P11.009.001) (Modulo)
• Istituto di matematica applicata e tecnologie informatiche \"Enrico Magenes\" (IMATI) (Istituto)

Autore CNR

• SARA PASQUALI (Unità di personale interno)
• FABRIZIO RUGGERI (Persona)

Insieme di parole chiave

• Keywords of "Bayesian inference for functional response in a stochastic predator-prey system" (Insieme di parole chiave)

Incoming links:

Prodotto

• Istituto di matematica applicata e tecnologie informatiche \"Enrico Magenes\" (IMATI) (Istituto)
• Modellizzazione di sistemi stocastici (ICT.P11.009.001) (Modulo)

Autore CNR di

• FABRIZIO RUGGERI (Persona)
• SARA PASQUALI (Unità di personale interno)

Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#rivistaDi

• Bulletin of mathematical biology (Rivista)

Insieme di parole chiave di

• Keywords of "Bayesian inference for functional response in a stochastic predator-prey system" (Insieme di parole chiave)