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oai:uvadoc.uva.es:10324/229202021-06-23T10:10:00Zcom_10324_1151com_10324_931com_10324_894col_10324_1278

Rueda Sabater, María Cristina 2017-03-31T09:08:29Z 2017-03-31T09:08:29Z 2013 Journal of Multivariate Analysis. Vol 117, pp: 88-99 http://uvadoc.uva.es/handle/10324/22920 10.1016/j.jmva.2013.02.001 The degrees of freedom of semiparametric additive monotone models are derived using results about projections onto sums of order cones. Two important related questions are also studied, namely, the de nition of estimators for the parameter of the error term and the formulation of speci c Akaike Information Criteria statistics. Several alternatives are proposed to solve both problems and simulation experiments are conducted to compare the behavior of the di erent candidates. A new selection criterion is proposed that combines the ability to guess the model but also the e ciency to estimate the variance parameter. Finally, the criterion is used to select the model in a regression problem from a well known data set. Ministerio de Ciencia e Innovación grant (MTM2012-37129) application/pdf eng info:eu-repo/semantics/openAccess http://creativecommons.org/licenses/by-nc-nd/4.0/ Elsevier Attribution-NonCommercial-NoDerivatives 4.0 International Degrees of freedom and model selection in semiparametric additive monotone regression info:eu-repo/semantics/article http://www.sciencedirect.com/science/article/pii/S0047259X13000158 SI