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Estimating monotonic rates from biological data using local linear regression.
Olito, Colin; White, Craig R; Marshall, Dustin J; Barneche, Diego R.
Afiliación
  • Olito C; Centre for Geometric Biology, School of Biological Sciences, Monash University, Clayton, VIC 3800, Australia colin.olito@gmail.com.
  • White CR; Centre for Geometric Biology, School of Biological Sciences, Monash University, Clayton, VIC 3800, Australia.
  • Marshall DJ; Centre for Geometric Biology, School of Biological Sciences, Monash University, Clayton, VIC 3800, Australia.
  • Barneche DR; Centre for Geometric Biology, School of Biological Sciences, Monash University, Clayton, VIC 3800, Australia.
J Exp Biol ; 220(Pt 5): 759-764, 2017 03 01.
Article en En | MEDLINE | ID: mdl-28049626
Accessing many fundamental questions in biology begins with empirical estimation of simple monotonic rates of underlying biological processes. Across a variety of disciplines, ranging from physiology to biogeochemistry, these rates are routinely estimated from non-linear and noisy time series data using linear regression and ad hoc manual truncation of non-linearities. Here, we introduce the R package LoLinR, a flexible toolkit to implement local linear regression techniques to objectively and reproducibly estimate monotonic biological rates from non-linear time series data, and demonstrate possible applications using metabolic rate data. LoLinR provides methods to easily and reliably estimate monotonic rates from time series data in a way that is statistically robust, facilitates reproducible research and is applicable to a wide variety of research disciplines in the biological sciences.
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Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Asunto principal: Consumo de Oxígeno / Metabolismo Basal / Aves / Simulación por Computador / Briozoos / Modelos Lineales / Modelos Biológicos Límite: Animals Idioma: En Revista: J Exp Biol Año: 2017 Tipo del documento: Article País de afiliación: Australia

Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Asunto principal: Consumo de Oxígeno / Metabolismo Basal / Aves / Simulación por Computador / Briozoos / Modelos Lineales / Modelos Biológicos Límite: Animals Idioma: En Revista: J Exp Biol Año: 2017 Tipo del documento: Article País de afiliación: Australia