The basis function approach for modeling autocorrelation in ecological data.

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.

journal_name

Ecology

journal_title

Ecology

authors

Hefley TJ,Broms KM,Brost BM,Buderman FE,Kay SL,Scharf HR,Tipton JR,Williams PJ,Hooten MB

doi

10.1002/ecy.1674

subject

Has Abstract

pub_date

2017-03-01 00:00:00

pages

632-646

issue

3

eissn

0012-9658

issn

1939-9170

journal_volume

98

pub_type

杂志文章

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