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

Author

Listed:
  • Eva Boj

    (Dept. de Matematica Economica, Financera i Actuarial, Univ. de Barcelona, Diagonal 690, 08034 Barcelona, Spain.)

  • Pedro Delicado

    (Universitat Politecnica de Catalunya)

  • Josep Fortiana

    (Universitat de Barcelona)

  • Anna Esteve

    (CEEISCAT)

  • Adria Caballe

    (Universitat Politecnica de Catalunya)

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.

Suggested Citation

  • Eva Boj & Pedro Delicado & Josep Fortiana & Anna Esteve & Adria Caballe, 2012. "Local Distance-Based Generalized Linear Models using the dbstats package for R," Working Papers XREAP2012-11, Xarxa de Referència en Economia Aplicada (XREAP), revised May 2012.
    • Handle: RePEc:xrp:wpaper:xreap2012-11
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    References listed on IDEAS

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    Cited by:

    1. Catalina Bolancé & Zuhair Bahraoui & Ramon Alemany, 2015. "Estimating extreme value cumulative distribution functions using bias-corrected kernel approaches," Working Papers XREAP2015-01, Xarxa de Referència en Economia Aplicada (XREAP), revised Jan 2015.
    2. Anna Castañer & Mª Mercè Claramunt, 2014. "Optimal stop-loss reinsurance: a dependence analysis," Working Papers XREAP2014-04, Xarxa de Referència en Economia Aplicada (XREAP), revised Apr 2014.
    3. Eva Boj & Teresa Costa & Josep Fortiana & Anna Esteve, 2015. "Assessing the Importance of Risk Factors in Distance-Based Generalized Linear Models," Methodology and Computing in Applied Probability, Springer, vol. 17(4), pages 951-962, December.
    4. Esther-Vayá & José-Ramón-García & Joaquim-Murillo & Javier-Romaní & Jordi-Suriñach, 2016. "“Economic Impact of Cruise Activity: The Port of Barcelona"," IREA Working Papers 201613, University of Barcelona, Research Institute of Applied Economics, revised Nov 2016.
    5. Mercedes Ayuso & Montserrat Guillen & Jens Perch Nielsen, 2019. "Improving automobile insurance ratemaking using telematics: incorporating mileage and driver behaviour data," Transportation, Springer, vol. 46(3), pages 735-752, June.
    6. Anna Castañer & Mª Mercè Claramunt & Alba Tadeo & Javier Varea, 2016. "Modelización de la dependencia del número de siniestros. Aplicación a Solvencia II," Working Papers XREAP2016-01, Xarxa de Referència en Economia Aplicada (XREAP), revised Sep 2016.
    7. Antonio Manresa & Ferran Sancho, 2012. "Leontief versus Ghosh: two faces of the same coin," Working Papers XREAP2012-18, Xarxa de Referència en Economia Aplicada (XREAP), revised Oct 2012.

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    Keywords

    Distance-based prediction; Generalized Linear Model; Local Likelihood; Iteratively Weighted Least Squares; R;
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