Parameter estimation in a simple stochastic differential equation for phytoplankton modelling
Publication: Research - peer-review › Journal 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-review › Journal article – Annual report year: 2011
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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 -