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Closed form Maximum Likelihood Estimator for Generalized Linear Models in the case of categorical explanatory variables: Application to insurance loss modelling

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  • معلومة اضافية
    • Contributors:
      Laboratoire Manceau de Mathématiques (LMM); Le Mans Université (UM); CEntre de REcherches en MAthématiques de la DEcision (CEREMADE); Université Paris Dauphine-PSL; Université Paris Sciences et Lettres (PSL)-Université Paris Sciences et Lettres (PSL)-Centre National de la Recherche Scientifique (CNRS); PANORisk
    • بيانات النشر:
      HAL CCSD
      Springer Verlag
    • الموضوع:
      2020
    • Collection:
      Université Paris-Dauphine: HAL
    • نبذة مختصرة :
      International audience ; Generalized Linear Models with categorical explanatory variables are considered and parameters of the model are estimated with an original exact maximum likelihood method. The existence of a sequence of maximum likelihood estimators is discussed and considerations on possible link functions are proposed. A focus is then given on two particular positive distributions: the Pareto 1 distribution and the shifted log-normal distributions. Finally, the approach is illustrated on a actuarial dataset to model insurance losses.
    • Relation:
      hal-01781504; https://hal.science/hal-01781504; https://hal.science/hal-01781504v3/document; https://hal.science/hal-01781504v3/file/GLM-2019-Hal.pdf
    • الرقم المعرف:
      10.1007/s00180-019-00918-7
    • Rights:
      info:eu-repo/semantics/OpenAccess
    • الرقم المعرف:
      edsbas.339019E3