Smoothing for spatiotemporal models and its application to modeling Muskrat-Mink interaction

Wenyang Zhang, Qiwei Yao, Howell Tong and Nils Chr Stenseth

LSE Research Online Documents on Economics from London School of Economics and Political Science, LSE Library

Abstract: 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.

Keywords: α-mixing; Canadian muskrat and mink data; fixed-domain asymptotics; food chain interaction; local linear regression; nugget effect; spatial smoothing; patiotemporal model; threshold model; time series (search for similar items in EconPapers)
JEL-codes: C1 (search for similar items in EconPapers)
Date: 2003-12
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Citations: View citations in EconPapers (6)

Published in Biometrics, December, 2003, 59(4), pp. 813-821. ISSN: 1541-0420

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Journal Article: Smoothing for Spatiotemporal Models and Its Application to Modeling Muskrat-Mink Interaction (2003)
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