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Please use this identifier to cite or link to this item: http://uvadoc.uva.es/handle/10324/22920
Title: Degrees of freedom and model selection in semiparametric additive monotone regression
Authors: Rueda, Cristina
Issue Date: 2013
Citation: Journal of Multivariate Analysis. Vol 117, pp: 88-99
Abstract: 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.
Peer Review: SI
DOI: 10.1016/j.jmva.2013.02.001
Sponsor: Ministerio de Ciencia e Innovación grant (MTM2012-37129)
Publisher Version: http://www.sciencedirect.com/science/article/pii/S0047259X13000158
Rights Owner: Elsevier
Language: eng
URI: http://uvadoc.uva.es/handle/10324/22920
Rights: info:eu-repo/semantics/openAccess
Appears in Collections:DEP24 - Artículos de revista

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