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

Autores
Cappa, Eduardo Pablo; Muñoz, Facundo; Sánchez, Leopoldo
Año de publicación
2019
Idioma
inglés
Tipo de recurso
artículo
Estado
versión publicada
Descripción
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.
Fil: Cappa, Eduardo Pablo. Instituto Nacional de Tecnología Agropecuaria (INTA). Instituto de Recursos Biológicos; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina
Fil: Muñoz, Facundo. Instituto Nacional de Investigación Agronómica. Unité Amélioration, Génétique et Physiologie Forestières; Francia
Fil: Sánchez, Leopoldo. Instituto Nacional de Investigación Agronómica. Unité Amélioration, Génétique et Physiologie Forestières; Francia
Fuente
Annals of forest science 76 : 53 (June 2019)
Materia
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
Nivel de accesibilidad
acceso restringido
Condiciones de uso
Repositorio
INTA Digital (INTA)
Institución
Instituto Nacional de Tecnología Agropecuaria
OAI Identificador
oai:localhost:20.500.12123/6222
Acceder
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oai_identifier_str oai:localhost:20.500.12123/6222
network_acronym_str INTADig
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network_name_str INTA Digital (INTA)
spelling Performance of alternative spatial models in empirical Douglas-fir and simulated datasetsCappa, Eduardo PabloMuñoz, FacundoSánchez, LeopoldoForest Genetic ResourcesMathematical ModelsRecursos Genéticos ForestalesPseudotsuga menziesiiModelos MatemáticosGlobal and Local Spatial TrendsAutoregressive ResidualTwo-dimensional P-splinesDouglas FirTendencias Espaciales Globales y LocalesResidual AutorregresivoSplines P bidimensionalesPino OregónAbeto de DouglasBased 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.Fil: Cappa, Eduardo Pablo. Instituto Nacional de Tecnología Agropecuaria (INTA). Instituto de Recursos Biológicos; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Muñoz, Facundo. Instituto Nacional de Investigación Agronómica. Unité Amélioration, Génétique et Physiologie Forestières; FranciaFil: Sánchez, Leopoldo. Instituto Nacional de Investigación Agronómica. Unité Amélioration, Génétique et Physiologie Forestières; FranciaSpringer2019-10-29T10:47:22Z2019-10-29T10:47:22Z2019-05-13info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfhttps://link.springer.com/article/10.1007%2Fs13595-019-0836-9http://hdl.handle.net/20.500.12123/62221286-4560https://doi.org/10.1007/s13595-019-0836-9Annals of forest science 76 : 53 (June 2019)reponame:INTA Digital (INTA)instname:Instituto Nacional de Tecnología Agropecuariaenginfo:eu-repo/semantics/restrictedAccess2025-09-18T10:07:45Zoai:localhost:20.500.12123/6222instacron:INTAInstitucionalhttp://repositorio.inta.gob.ar/Organismo científico-tecnológicoNo correspondehttp://repositorio.inta.gob.ar/oai/requesttripaldi.nicolas@inta.gob.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:l2025-09-18 10:07:45.864INTA Digital (INTA) - Instituto Nacional de Tecnología Agropecuariafalse
dc.title.none.fl_str_mv Performance of alternative spatial models in empirical Douglas-fir and simulated datasets
title Performance of alternative spatial models in empirical Douglas-fir and simulated datasets
spellingShingle Performance of alternative spatial models in empirical Douglas-fir and simulated datasets
Cappa, Eduardo Pablo
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
title_short Performance of alternative spatial models in empirical Douglas-fir and simulated datasets
title_full Performance of alternative spatial models in empirical Douglas-fir and simulated datasets
title_fullStr Performance of alternative spatial models in empirical Douglas-fir and simulated datasets
title_full_unstemmed Performance of alternative spatial models in empirical Douglas-fir and simulated datasets
title_sort Performance of alternative spatial models in empirical Douglas-fir and simulated datasets
dc.creator.none.fl_str_mv Cappa, Eduardo Pablo
Muñoz, Facundo
Sánchez, Leopoldo
author Cappa, Eduardo Pablo
author_facet Cappa, Eduardo Pablo
Muñoz, Facundo
Sánchez, Leopoldo
author_role author
author2 Muñoz, Facundo
Sánchez, Leopoldo
author2_role author
author
dc.subject.none.fl_str_mv 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
topic 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
dc.description.none.fl_txt_mv 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.
Fil: Cappa, Eduardo Pablo. Instituto Nacional de Tecnología Agropecuaria (INTA). Instituto de Recursos Biológicos; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina
Fil: Muñoz, Facundo. Instituto Nacional de Investigación Agronómica. Unité Amélioration, Génétique et Physiologie Forestières; Francia
Fil: Sánchez, Leopoldo. Instituto Nacional de Investigación Agronómica. Unité Amélioration, Génétique et Physiologie Forestières; Francia
description 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.
publishDate 2019
dc.date.none.fl_str_mv 2019-10-29T10:47:22Z
2019-10-29T10:47:22Z
2019-05-13
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
http://purl.org/coar/resource_type/c_6501
info:ar-repo/semantics/articulo
format article
status_str publishedVersion
dc.identifier.none.fl_str_mv https://link.springer.com/article/10.1007%2Fs13595-019-0836-9
http://hdl.handle.net/20.500.12123/6222
1286-4560
https://doi.org/10.1007/s13595-019-0836-9
url 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
identifier_str_mv 1286-4560
dc.language.none.fl_str_mv eng
language eng
dc.rights.none.fl_str_mv info:eu-repo/semantics/restrictedAccess
eu_rights_str_mv restrictedAccess
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv Springer
publisher.none.fl_str_mv Springer
dc.source.none.fl_str_mv Annals of forest science 76 : 53 (June 2019)
reponame:INTA Digital (INTA)
instname:Instituto Nacional de Tecnología Agropecuaria
reponame_str INTA Digital (INTA)
collection INTA Digital (INTA)
instname_str Instituto Nacional de Tecnología Agropecuaria
repository.name.fl_str_mv INTA Digital (INTA) - Instituto Nacional de Tecnología Agropecuaria
repository.mail.fl_str_mv tripaldi.nicolas@inta.gob.ar
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score 13.000565

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