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- Title
Bayesian Estimation of Power Law Function in Nonhomogeneous Poisson Process Applied in Mosul Gas Power Plant – Iraq.
- Authors
Alsultan, Fatimah Abdulrazzaq; Sulaiman, Muthanna Subhi
- Abstract
Non-homogeneous Poisson process with power law intensity function has often been used as a model for describing the failure pattern of repairable systems. Maximum likelihood and Bayesian estimation are used to estimate model parameters. Simulation and realistic application are used and represented by shutting down the gas power plant in Mosul. Stops in hours are designed with the power law random process model in order to obtain a model that represents the average stop time of the units throughout the study period in the best way. The results of the application on the data of the three concerned stations show that the Bayes estimate is better than the maximum likelihood estimate. This proves that the Bayes methods are very accurate and effective in estimating the rate of occurrence parameters.
- Subjects
MOSUL (Iraq); IRAQ; POISSON processes; GAS power plants; MAXIMUM likelihood statistics; COMPUTER performance; STOCHASTIC processes; UNITS of time
- Publication
Iraqi Journal of Science, 2024, Vol 65, Issue 5, p2596
- ISSN
0067-2904
- Publication type
Article
- DOI
10.24996/ijs.2024.65.5.20