Study on the transform method of estimating discrete frequency from continuous variable: ratemaking for car repair insurance based on SAS system coding

  • Yuantao Xie
  • Huijuan Lv
  • Xiaoke Sun
  • Yu Mao
  • Juan Yang


Some discrete variable such as frequency cannot be estimated when a limited sample is drawn from the population which is not sufficient enough to represent the whole population. But the procedure records data from finite samples that can be converted to frequency estimates through computer intensive calculations. The aim of this paper is to develop an Accelerated Failure Time model for the continuous variables such as survival times or the first breakdown mileage by embedding Weibull distribution into a GLMs structure. Then we can derive the hazard ratio function and transform the continuous variable modeling into discrete variable inference. A numerical illustration based on a data derived from a Chinese auto dealer is performed with the statistical software SAS. The rate was made for different types of vehicles and their different parts based on the minimum repairing and the purchase of car repairing insurance for a certain time.


Generalized linear models Hazard ratio function Frequency inference Accelerated failure time 



The paper was financially supported by the National Social Science Foundation of China “Individual Risk Assessment under the background of Risk Information Share” under Grant No. 71303045 and “the Fundamental Research Funds for the Central Universities” in UIBE (CXTD9-04), and the People’s Insurance Company of China Disaster Research Fund.


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© Springer Science+Business Media, LLC, part of Springer Nature 2018

Authors and Affiliations

  1. 1.School of Insurance and EconomicsUniversity of International Business and EconomicsBeijingChina
  2. 2.Institute of Comprehensive DevelopmentChinese Academy of Science and Technology for DevelopmentBeijingChina

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