Performance of alternative spatial models in empirical Douglas-fir and simulated datasets
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.
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| Main Authors: | , , |
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| Format: | info:ar-repo/semantics/artículo biblioteca |
| Language: | eng |
| Published: |
Springer
2019-05-13
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| Subjects: | Forest Genetic Resources, Mathematical Models, Recursos Genéticos Forestales, Pseudotsuga menziesii, Modelos Matemáticos, Global and Local Spatial Trends, Autoregressive Residual, Two-dimensional P-splines, Douglas Fir, Tendencias Espaciales Globales y Locales, Residual Autorregresivo, Splines P bidimensionales, Pino Oregón, Abeto de Douglas, |
| Online Access: | https://link.springer.com/article/10.1007%2Fs13595-019-0836-9 http://hdl.handle.net/20.500.12123/6222 https://doi.org/10.1007/s13595-019-0836-9 |
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