The basis function approach for modeling autocorrelation in ecological data

Ecology
By: , and 

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Abstract

Analyzing ecological data often requires modeling the autocorrelation created by spatial and temporal processes. Many seemingly disparate statistical methods used to account for autocorrelation can be expressed as regression models that include basis functions. Basis functions also enable ecologists to modify a wide range of existing ecological models in order to account for autocorrelation, which can improve inference and predictive accuracy. Furthermore, understanding the properties of basis functions is essential for evaluating the fit of spatial or time-series models, detecting a hidden form of collinearity, and analyzing large data sets. We present important concepts and properties related to basis functions and illustrate several tools and techniques ecologists can use when modeling autocorrelation in ecological data.

Additional publication details

Publication type Article
Publication Subtype Journal Article
Title The basis function approach for modeling autocorrelation in ecological data
Series title Ecology
DOI 10.1002/ecy.1674
Volume 98
Issue 3
Year Published 2017
Language English
Publisher Ecological Society of America
Contributing office(s) Coop Res Unit Seattle
Description 15 p.
First page 632
Last page 646