Fitting matrix geometric distributions by model reduction
Date
2015
Authors
Akar, N.
Editor(s)
Advisor
Supervisor
Co-Advisor
Co-Supervisor
Instructor
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
Journal Title
Journal ISSN
Volume Title
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1
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17
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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