Proceedings of the 2015 International Conference on Electrical, Automation and Mechanical Engineering

Parameters Estimation of Three Mixed Exponential Distributions

Authors
G.Q. Zhang
Corresponding Author
G.Q. Zhang
Available Online July 2015.
DOI
10.2991/eame-15.2015.155How to use a DOI?
Keywords
mixed exponential distribution; ECM algorithm; MC simulation
Abstract

Mixed exponential distributions play an important role in life time data analysis, but if we use traditional statistical methods to estimate the parameters in the model, it will be very difficult, however we apply the generalized expectation maximization (GEM) algorithm, namely expectation conditional maximization (ECM) algorithm, to estimate the parameters of the model, it will greatly simplify the complexity of the calculation. In this paper, we study the parameter estimation problem in complete data situation, and give Monte Carlo (MC) simulation, which results show that the algorithm based on ECM to estimate the parameters of the mixed exponential distribution is very effective.

Copyright
© 2015, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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Volume Title
Proceedings of the 2015 International Conference on Electrical, Automation and Mechanical Engineering
Series
Advances in Engineering Research
Publication Date
July 2015
ISBN
10.2991/eame-15.2015.155
ISSN
2352-5401
DOI
10.2991/eame-15.2015.155How to use a DOI?
Copyright
© 2015, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

Cite this article

TY  - CONF
AU  - G.Q. Zhang
PY  - 2015/07
DA  - 2015/07
TI  - Parameters Estimation of Three Mixed Exponential Distributions
BT  - Proceedings of the 2015 International Conference on Electrical, Automation and Mechanical Engineering
PB  - Atlantis Press
SP  - 551
EP  - 553
SN  - 2352-5401
UR  - https://doi.org/10.2991/eame-15.2015.155
DO  - 10.2991/eame-15.2015.155
ID  - Zhang2015/07
ER  -