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A fitting method with generalized Erlang distributions

Lookup NU author(s): Dr Nigel Thomas

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Abstract

We present a fitting technique that fits trace data into a generalized Erlang distribution class using an EM method. A generalized Erlang (GEr) distribution can be made by convolution of the third order ME distributions similar to the formulation of an Erlang distribution with exponential distributions. We give a sufficient condition for the representation to make a probability density function and we implement a fitting algorithm into a GEr distribution set by solving a nonlinear optimization problem with the EM algorithm. The effectiveness of the proposed fitting algorithm is presented by applying fitting methods to sets of synthetic data and measurement data. We present comparative numerical simulation results of our approach and other methods.

Publication metadata

Author(s): Kim K, Thomas N

Publication type: Article

Publication status: Published

Journal: Simulation Modelling Practice and Theory

Year: 2011

Volume: 19

Issue: 7

Pages: 1507-1517

Print publication date: 21/03/2011

ISSN (print): 1569-190X

Publisher: Elsevier BV

URL: http://dx.doi.org/10.1016/j.simpat.2011.03.003

DOI: 10.1016/j.simpat.2011.03.003

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