A comparative study between nonlinear regression and nonparametric approaches for modellingPhalaris paradoxaseedling emergence
| Autor: | J. M. Urbano, Mario Francisco-Fernández, Frank Forcella, Ricardo Cao, José Luis González-Andújar, Fernando Bastida, Miguel Reyes |
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| Přispěvatelé: | Ministerio de Ciencia e Innovación (España), European Commission, Ministerio de Economía y Competitividad (España) |
| Rok vydání: | 2016 |
| Předmět: |
0106 biological sciences
Mean squared error Gompertz function Plant Science 01 natural sciences Statistics Logistic Weed emergence model Phalaris paradoxa Ecology Evolution Behavior and Systematics Parametric statistics Mathematics Weibull distribution biology Cumulative distribution function Nonparametric statistics Awned canary grass 04 agricultural and veterinary sciences biology.organism_classification Hood canary grass Hydrothermal time Gompertz 040103 agronomy & agriculture 0401 agriculture forestry and fisheries Weibull Agronomy and Crop Science Nonlinear regression Distribution functions 010606 plant biology & botany |
| Zdroj: | Digital.CSIC. Repositorio Institucional del CSIC instname |
| ISSN: | 0043-1737 |
| DOI: | 10.1111/wre.12216 |
| Popis: | Parametric nonlinear regression (PNR) models are used widely to fit weed seedling emergence patterns to soil microclimatic indices. However, such approximation has been questioned, mainly due to several statistical limitations. Alternatively, nonparametric approaches can be used to overcome the problems presented by PNR models. Here, we used an emergence data set of Phalaris paradoxa to compare both approaches. Mean squared error and correlation results indicated higher accuracy for the descriptive ability but similar poor performance for predictive ability of the nonparametric approach in comparison with the PNR approach. These results suggest that our nonparametric cumulative distribution function approach is a valuable alternative to the classical parametric nonlinear regression models to describe complex emergence patterns for P. paradoxa, but not to predict them. This research has been partially supported by the Spanish Ministry of Science and Innovation Grant MTM2011-22392 and MTM2014-52876-R for the second, third and fourth authors and by FEDER (European Regional Development Fund) and the Spanish Ministry of Economy and Competitiveness Grant AGL2012-33736 for the first and last authors. |
| Databáze: | OpenAIRE |
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