2011
DOI: 10.1007/s13253-010-0049-z
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Functional Data Analysis in Ecosystem Research: The Decline of Oweekeno Lake Sockeye Salmon and Wannock River Flow

Abstract: Functional regression is a natural tool for exploring the potential impact of the physical environment (continuously monitored) on biological processes (often only assessed annually). This paper explores the potential use of functional regression analysis and the closely related functional principal component analysis for studying the relationship between river flow (continuously monitored) and salmon abundance (measured annually). The specific example involves a depressed sockeye salmon population in Rivers I… Show more

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Cited by 18 publications
(12 citation statements)
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“…In such cases a B-spline curve can be used to define the hydrograph as a functional predictor variable (e.g. Ainsworth et al, 2011). B-spline curves, which are a series of joined polynomial functions, offer great flexibility in quantifying the functional form of time series data (Ramsay and Silverman, 2006).…”
Section: Functional Linear Modelsmentioning
confidence: 99%
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“…In such cases a B-spline curve can be used to define the hydrograph as a functional predictor variable (e.g. Ainsworth et al, 2011). B-spline curves, which are a series of joined polynomial functions, offer great flexibility in quantifying the functional form of time series data (Ramsay and Silverman, 2006).…”
Section: Functional Linear Modelsmentioning
confidence: 99%
“…A functional linear model provides an efficient alternative to summarise the time series into a smaller number of basis functions, however, the potential for overfitting still exists with functional linear models. Therefore, the challenge is to use a functional regression coefficient that is sufficiently complex to capture relationships between the response variable and the time series of the predictor, yet is simple enough to interpret and not result in an overfit model (Ramsay et al, 2010;Ainsworth et al, 2011). As is common in most statistical models, this amounts to finding the trade-off between detecting signal from noise.…”
Section: Functional Linear Modelsmentioning
confidence: 99%
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“…In this note, we use wavelets to model temporal activity data as curves in the context of functional data analysis (FDA [32] [33] [34] [35]). One may argue the case for treating these temporal activity data as vector-valued data.…”
Section: Introductionmentioning
confidence: 99%