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      Fitting matrix geometric distributions by model reduction

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      Author
      Akar, N.
      Date
      2015
      Source Title
      Stochastic Models
      Print ISSN
      1532-6349
      Electronic ISSN
      1532-4214
      Publisher
      Taylor and Francis Inc.
      Volume
      31
      Issue
      2
      Pages
      292 - 315
      Language
      English
      Type
      Article
      Item Usage Stats
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      Abstract
      A novel algorithmic method is proposed to fit matrix geometric distributions of desired order to empirical data or arbitrary discrete distributions. The proposed method effectively combines two existing approaches from two different disciplines: well-established model reduction methods used in system theory and moment matching methods of applied probability that employ second-order discrete phase-type distributions. The proposed approach is validated with exhaustive numerical examples including well-known statistical data. Copyright
      Keywords
      Discrete phase type distribution
      Matrix geometric distribution
      Model reduction
      Algorithms
      Geometry
      Matrix algebra
      Algorithmic methods
      Applied probability
      Discrete distribution
      Matrix-geometric
      Model reduction method
      Moment matching method
      Probability distributions
      Permalink
      http://hdl.handle.net/11693/22714
      Published Version (Please cite this version)
      http://dx.doi.org/10.1080/15326349.2014.1003271
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      • Department of Electrical and Electronics Engineering 3524
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