An Iterated Local Search Algorithm for Estimating the Parameters of the Gamma/Gompertz Distribution | Zendy

Behrouz Afshar-Nadjafi | Zendy

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An Iterated Local Search Algorithm for Estimating the Parameters of the Gamma/Gompertz Distribution

Author(s) -

Behrouz Afshar-Nadjafi

Publication year - 2014

Publication title -

modelling and simulation in engineering

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 0.264

H-Index - 20

eISSN - 1687-5591

pISSN - 1687-5605

DOI - 10.1155/2014/629693

Subject(s) - gompertz function , gamma distribution , iterated local search , iterated function , mathematics , maximum likelihood , distribution (mathematics) , algorithm , estimation , estimation theory , likelihood function , distribution fitting , mathematical optimization , generalized gamma distribution , statistics , computer science , probability distribution , local search (optimization) , engineering , mathematical analysis , systems engineering

Extensive research has been devoted to the estimation of the parameters of frequently used distributions. However, little attention has been paid to estimation of parameters of Gamma/Gompertz distribution, which is often encountered in customer lifetime and mortality risks distribution literature. This distribution has three parameters. In this paper, we proposed an algorithm for estimating the parameters of Gamma/Gompertz distribution based on maximum likelihood estimation method. Iterated local search (ILS) is proposed to maximize likelihood function. Finally, the proposed approach is computationally tested using some numerical examples and results are analyzed

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