Local Distance-Based Generalized Linear Models using the dbstats package for R

Eva Boj, Pedro Delicado, Josep Fortiana, Anna Esteve and Adria Caballe
Additional contact information
Josep Fortiana: Universitat de Barcelona
Anna Esteve: CEEISCAT
Adria Caballe: Universitat Politecnica de Catalunya

No XREAP2012-11, Working Papers from Xarxa de Referència en Economia Aplicada (XREAP)

Abstract: This paper introduces local distance-based generalized linear models. These models extend (weighted) distance-based linear models firstly with the generalized linear model concept, then by localizing. Distances between individuals are the only predictor information needed to fit these models. Therefore they are applicable to mixed (qualitative and quantitative) explanatory variables or when the regressor is of functional type. Models can be fitted and analysed with the R package dbstats, which implements several distancebased prediction methods.

Keywords: Distance-based prediction; Generalized Linear Model; Local Likelihood; Iteratively Weighted Least Squares; R (search for similar items in EconPapers)
Pages: 56 pages
Date: 2012-05, Revised 2012-05
New Economics Papers: this item is included in nep-ecm and nep-for
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Citations: View citations in EconPapers (7)

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http://www.xreap.cat/RePEc/xrp/pdf/XREAP2012-11.pdf First version, 2012 (application/pdf)
http://www.xreap.cat/RePEc/xrp/pdf/XREAP2012-11.pdf Revised version, 2012 (application/pdf)

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