dc.creatorCorrales Alvarez, J. D.
dc.creatorMunilla, S.
dc.creatorCantet, Rodolfo Juan Carlos
dc.date.accessioned2017-05-19T19:31:45Z
dc.date.accessioned2018-11-06T15:50:56Z
dc.date.available2017-05-19T19:31:45Z
dc.date.available2018-11-06T15:50:56Z
dc.date.created2017-05-19T19:31:45Z
dc.date.issued2015-08
dc.identifierCorrales Alvarez, J. D.; Munilla, S.; Cantet, Rodolfo Juan Carlos; Polynomial order selection in random regression models via penalizing adaptively the likelihood; Wiley; Journal Of Animal Breeding And Genetics-zeitschrift Fur Tierzuchtung Und Zuchtungsbiologie; 132; 4; 8-2015; 281-288
dc.identifier0931-2668
dc.identifierhttp://hdl.handle.net/11336/16761
dc.identifier.urihttp://repositorioslatinoamericanos.uchile.cl/handle/2250/1901838
dc.description.abstractOrthogonal Legendre polynomials (LP) are used to model the shape of additive genetic and permanent environmental effects in random regression models (RRM). Frequently, the Akaike (AIC) and the Bayesian (BIC) information criteria are employed to select LP order. However, it has been theoretically shown that neither AIC nor BIC is simultaneously optimal in terms of consistency and efficiency. Thus, the goal was to introduce a method, ‘penalizing adaptively the likelihood’ (PAL), as a criterion to select LP order in RRM. Four simulated data sets and real data (60 513 records, 6675 Colombian Holstein cows) were employed. Nested models were fitted to the data, and AIC, BIC and PAL were calculated for all of them. Results showed that PAL and BIC identified with probability of one the true LP order for the additive genetic and permanent environmental effects, but AIC tended to favour over parameterized models. Conversely, when the true model was unknown, PAL selected the best model with higher probability than AIC. In the latter case, BIC never favoured the best model. To summarize, PAL selected a correct model order regardless of whether the ‘true’ model was within the set of candidates.
dc.languageeng
dc.publisherWiley
dc.relationinfo:eu-repo/semantics/altIdentifier/doi/http://dx.doi.org/10.1111/jbg.12130
dc.relationinfo:eu-repo/semantics/altIdentifier/url/http://onlinelibrary.wiley.com/doi/10.1111/jbg.12130/abstract
dc.rightshttps://creativecommons.org/licenses/by-nc-sa/2.5/ar/
dc.rightsinfo:eu-repo/semantics/restrictedAccess
dc.subjectLegendre polynomial
dc.subjectModel selection
dc.subjectPenalizing adaptively the likelihood
dc.subjectRandom regressions
dc.titlePolynomial order selection in random regression models via penalizing adaptively the likelihood
dc.typeArtículos de revistas
dc.typeArtículos de revistas
dc.typeArtículos de revistas


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