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Kalman filter initialization for integrated population modelling
Author(s) -
Besbeas Panagiotis,
Morgan Byron J. T.
Publication year - 2012
Publication title -
journal of the royal statistical society: series c (applied statistics)
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.205
H-Index - 72
eISSN - 1467-9876
pISSN - 0035-9254
DOI - 10.1111/j.1467-9876.2011.01012.x
Subject(s) - initialization , kalman filter , computer science , population , multivariate statistics , component (thermodynamics) , series (stratigraphy) , data assimilation , filter (signal processing) , statistics , mathematics , geography , artificial intelligence , machine learning , biology , meteorology , paleontology , demography , sociology , programming language , physics , computer vision , thermodynamics
Summary. In integrated population modelling in ecology, where data from multiple surveys are analysed simultaneously, the Kalman filter may be used to approximate a component likelihood for a state space model of population count data. We evaluate a new method for initiating this Kalman filter, based on a stable age distribution. The new method is illustrated and compared with alternative approaches by application to data on the grey heron. The new method is simple to use, extends naturally to the case of multivariate time series of count data and performs well in a simulation study.