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Performance of alternative spatial models in empirical Douglas-fir and simulated datasets

Resumen
Based on an empirical dataset originating from the French Douglas-fir breeding program, we showed that the bidimensional autoregressive and the two-dimensional P-spline regression spatial models clearly outperformed the classical block model, in terms of both goodness of fit and predicting ability. In contrast, the differences between both spatial models were relatively small. In general, results from simulated data were well in agreement with those from [ver mas...]
Based on an empirical dataset originating from the French Douglas-fir breeding program, we showed that the bidimensional autoregressive and the two-dimensional P-spline regression spatial models clearly outperformed the classical block model, in terms of both goodness of fit and predicting ability. In contrast, the differences between both spatial models were relatively small. In general, results from simulated data were well in agreement with those from empirical data. [Cerrar]
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Autor
Cappa, Eduardo Pablo;   Muñoz, Facundo;   Sánchez, Leopoldo;  
Fuente
Annals of forest science 76 : 53 (June 2019)
Fecha
2019-05-13
Editorial
Springer
ISSN
1286-4560
URI
https://link.springer.com/article/10.1007%2Fs13595-019-0836-9
http://hdl.handle.net/20.500.12123/6222
DOI
https://doi.org/10.1007/s13595-019-0836-9
Formato
pdf
Tipo de documento
artículo
Palabras Claves
Forest Genetic Resources; Recursos Genéticos Forestales; Pseudotsuga menziesii; Modelos Matemáticos; Mathematical Models; Global and Local Spatial Trends; Tendencias Espaciales Globales y Locales; Autoregressive Residual; Residual Autorregresivo; Two-dimensional P-splines; Splines P bidimensionales; Pino Oregón; Abeto de Douglas; Douglas Fir;
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Excepto donde se diga explicitamente, este item se publica bajo la siguiente descripción: Creative Commons Attribution-NonCommercial-ShareAlike 2.5 Unported (CC BY-NC-SA 2.5)
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