Parameter estimation in a simple stochastic differential equation for phytoplankton modelling

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

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Parameter estimation in a simple stochastic differential equation for phytoplankton modelling. / Møller, Jan Kloppenborg; Madsen, Henrik; Carstensen, Jacob.

In: Ecological Modelling, Vol. 222, No. 11, 2011, p. 1793-1799.

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

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Author

Møller, Jan Kloppenborg; Madsen, Henrik; Carstensen, Jacob / Parameter estimation in a simple stochastic differential equation for phytoplankton modelling.

In: Ecological Modelling, Vol. 222, No. 11, 2011, p. 1793-1799.

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

Bibtex

@article{f90b3c4f18474c68b1bcf63f85643b19,
title = "Parameter estimation in a simple stochastic differential equation for phytoplankton modelling",
keywords = "Extended Kalman Filter, Phytoplankton modelling, Parameter estimation, Maximum likelihood estimation, Stochastic differential equations",
publisher = "Elsevier BV",
author = "Møller, {Jan Kloppenborg} and Henrik Madsen and Jacob Carstensen",
year = "2011",
doi = "10.1016/j.ecolmodel.2011.03.025",
volume = "222",
number = "11",
pages = "1793--1799",
journal = "Ecological Modelling",
issn = "0304-3800",

}

RIS

TY - JOUR

T1 - Parameter estimation in a simple stochastic differential equation for phytoplankton modelling

A1 - Møller,Jan Kloppenborg

A1 - Madsen,Henrik

A1 - Carstensen,Jacob

AU - Møller,Jan Kloppenborg

AU - Madsen,Henrik

AU - Carstensen,Jacob

PB - Elsevier BV

PY - 2011

Y1 - 2011

N2 - 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.

AB - 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.

KW - Extended Kalman Filter

KW - Phytoplankton modelling

KW - Parameter estimation

KW - Maximum likelihood estimation

KW - Stochastic differential equations

U2 - 10.1016/j.ecolmodel.2011.03.025

DO - 10.1016/j.ecolmodel.2011.03.025

JO - Ecological Modelling

JF - Ecological Modelling

SN - 0304-3800

IS - 11

VL - 222

SP - 1793

EP - 1799

ER -