Authors: Christmann, Andreas
Marin-Galiano, Marcos
Title: Insurance: an R-Program to Model Insurance Data
Language (ISO): en
Abstract: Data sets from car insurance companies often have a high-dimensional complex dependency structure. The use of classical statistical methods such as generalized linear models or Tweedie’s compound Poisson model can yield problems in this case. Christmann (2004) proposed a general approach to model the pure premium by exploiting characteristic features of such data sets. In this paper we describe a program to use this approach based on a combination of multinomial logistic regression and epsilon-support vector regression from modern statistical machine learning.
Subject Headings: claim size
insurance tariff
logistic regression
statistical machine learning
support vector regression
URI: http://hdl.handle.net/2003/5301
http://dx.doi.org/10.17877/DE290R-6724
Issue Date: 2004
Publisher: Universität Dortmund
Appears in Collections:Sonderforschungsbereich (SFB) 475

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