Fitting matrix geometric distributions by model reduction
Author
Akar, N.
Date
2015Source 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
ArticleItem Usage Stats
110
views
views
89
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downloads
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 distributionMatrix 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/11693/22714Published Version (Please cite this version)
http://dx.doi.org/10.1080/15326349.2014.1003271Collections
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