Investigating the efficiency of fitting Coxian phase-type distributions to health care data

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Coxian phase-type distributions are becoming a popular means of representing survival times within a health care environment. They are favoured as they show a distribution as a system of phases and can allow for an easy visual representation of the rate of flow of patients through a system. Difficulties arise, however, in determining the parameter estimates of the Coxian phase-type distribution. This paper examines ways of making the fitting of the Coxian phase-type distribution less cumbersome by outlining different software packages and algorithms available to perform the fit and assessing their capabilities through a number of performance measures. The performance measures rate each of the methods and help in identifying the more efficient. Conclusions drawn from these performance measures suggest SAS to be the most robust package. It has a high rate of convergence in each of the four example model fits considered, short computational times, detailed output, convergence criteria options, along with a succinct ability to switch between different algorithms.
Original languageEnglish
Pages (from-to)133-145
Number of pages13
JournalIMA Journal of Management Mathematics
Issue number2
Publication statusPublished - Apr 2012


  • Coxian phase-type distributions fitting parameter estimation optimization health care data

ASJC Scopus subject areas

  • Applied Mathematics
  • Management Information Systems
  • Strategy and Management


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