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Smoothing for Spatiotemporal Models and Its Application to Modeling Muskrat‐Mink Interaction
Author(s) -
Zhang Wenyang,
Yao Qiwei,
Tong Howell,
Chr. Stenseth Nils
Publication year - 2003
Publication title -
biometrics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.298
H-Index - 130
eISSN - 1541-0420
pISSN - 0006-341X
DOI - 10.1111/j.0006-341x.2003.00095.x
Subject(s) - smoothing , mink , computer science , set (abstract data type) , sample (material) , ecology , biology , chemistry , chromatography , computer vision , programming language
Summary . For a set of spatially dependent dynamical models, we propose a method for estimating parameters that control temporal dynamics by spatial smoothing. The new approach is particularly relevant for analyzing spatially distributed panels of short time series. The asymptotic results show that spatial smoothing will improve the estimation in the presence of nugget effect, even when the sample size in each location is large. The proposed methodology is used to analyze the annual mink and muskrat data collected in a period of 25 years in 81 Canadian locations. Based on the proposed method, we are able to model the temporal dynamics which reflects the food chain interaction of the two species.