Parameter estimation in a simple stochastic differential equation for phytoplankton modelling

Publication: Research - peer-reviewJournal article – Annual report year: 2011

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The use of stochastic differential equations (SDEs) for simulation of aquatic ecosystems has attracted increasing attention in recent years. The SDE setting also provides the opportunity for statistical estimation of ecosystem parameters. We present an estimation procedure, based on Kalman filtering and likelihood estimation, which has proven useful in other fields of application. The estimation procedure is presented and the development from ordinary differential equations (ODEs) to SDEs is discussed with emphasis on autocorrelated residuals, commonly encountered with ODEs. The estimation procedure is applied to a simple nitrogen-phytoplankton model, with data from a Danish estuary (1988-2006). The resulting SDE is simple enough to have a well-known stationary distribution and this distribution is presented.
Original languageEnglish
JournalEcological Modelling
Publication date2011
Volume222
Issue11
Pages1793-1799
ISSN0304-3800
DOIs
StatePublished
CitationsWeb of Science® Times Cited: 2

Keywords

  • Extended Kalman Filter, Phytoplankton modelling, Parameter estimation, Maximum likelihood estimation, Stochastic differential equations
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