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oai:recercat.cat:2445/1043352025-12-05T05:55:32Zcom_2072_1057col_2072_478917col_2072_478919

Global and local distance-based generalized linear models Boj del Val, Eva Caballé Mestres, Adrià Delicado, Pedro Esteve, Anna Fortiana Gregori, Josep Models lineals (Estadística) Estimació d'un paràmetre Linear models (Statistics) Parameter estimation This paper introduces local distance-based generalized linear models. These models extend (weighted) distance-based linear models first to the generalized linear model framework. Then, a nonparametric version of these models is proposed by means of local fitting. Distances between individuals are the only predictor information needed to fit these models. Therefore, they are applicable, among others, to mixed (qualitative and quantitative) explanatory variables or when the regressor is of functional type. An implementation is provided by the R package dbstats, which also implements other distance-based prediction methods. Supplementary material for this article is available online, which reproduces all the results of this article. 2016-12-01T10:12:24Z 2017-04-07T22:01:23Z 2016-03 2016-12-01T10:12:29Z info:eu-repo/semantics/article info:eu-repo/semantics/acceptedVersion 1133-0686 https://hdl.handle.net/2445/104335 654281 eng Versió postprint del document publicat a: https://doi.org/10.1007/s11749-015-0447-1 TEST, 2016, vol. 25, p. 170-195 https://doi.org/10.1007/s11749-015-0447-1 (c) Springer Verlag, 2016 info:eu-repo/semantics/openAccess 26 p. application/pdf Springer Verlag Articles publicats en revistes (Matemàtica Econòmica, Financera i Actuarial)