Advances in Computational Design

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Fitting acyclic phase-type distributions by orthogonal distance

  • Pulungan, Reza (Department of Computer Science and Electronics, Faculty of Mathematics and Natural Sciences, Universitas Gadjah Mada) ;
  • Hermanns, Holger (Dependable Systems and Software, Saarland University)
  • Received : 2021.07.12
  • Accepted : 2021.11.12
  • Published : 2022.01.25
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Abstract

Phase-type distributions are the distributions of the time to absorption in finite and absorbing Markov chains. They generalize, while at the same time, retain the tractability of the exponential distributions and their family. They are widely used as stochastic models from queuing theory, reliability, dependability, and forecasting, to computer networks, security, and computational design. The ability to fit phase-type distributions to intractable or empirical distributions is, therefore, highly desirable for many practical purposes. Many methods and tools currently exist for this fitting problem. In this paper, we present the results of our investigation on using orthogonal-distance fitting as a method for fitting phase-type distributions, together with a comparison to the currently existing fitting methods and tools.

Keywords

Acknowledgement

This work was supported by Hibah Penelitian Dosen Departemen Ilmu Komputer dan Elektronika, Fakultas Matematika dan Ilmu Pengetahuan Alam, Universitas Gadjah Mada. This work was also partially supported by the ERC Advanced Investigators Grant 695614 (POWVER), by the German Research Foundation (DFG) under grant No. 389792660, as part of TRR 248, see https://perspicuous-computing.science, and by the Key-Area Research and Development Program of Guangdong Province (Grant 2018B010107004).

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