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 |
Provenance: | Universität Dortmund |
Appears in Collections: | Sonderforschungsbereich (SFB) 475 |
This item is protected by original copyright |
This item is protected by original copyright rightsstatements.org