Parameter Estimation in Multivariate Gamma Distribution

  • V S Vaidyanathan Pondicherry University Puducherry, India
  • R Vani Lakshmi Pondicherry University, India
DOI: https://doi.org/10.19139/soic.v3i2.95

Abstract

Multivariate gamma distribution finds abundant applications in stochastic modelling, hydrology and reliability. Parameter estimation in this distribution is a challenging one as it involves many parameters to be estimated simultaneously. In this paper, the form of multivariate gamma distribution proposed by Mathai and Moschopoulos [10] is considered. This form has nice properties in terms of marginal and conditional densities. A new method of estimation based on optimal search is proposed for estimating the parameters using the marginal distributions and the concepts of maximum likelihood, spacings and least squares. The proposed methodology is easy to implement and is free from calculus. It optimizes the objective function by searching over a wide range of values and determines the estimate of the parameters. The consistency of the estimates is demonstrated in terms of mean, standard deviation and mean square error through simulation studies for different choices of parameters. 

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Published
2015-05-12
How to Cite
Vaidyanathan, V. S., & Vani Lakshmi, R. (2015). Parameter Estimation in Multivariate Gamma Distribution. Statistics, Optimization & Information Computing, 3(2), 147-159. https://doi.org/10.19139/soic.v3i2.95
Issue
Vol 3 No 2 (2015)
Section
Research Articles
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