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Journal of Applied Sciences
  Year: 2016 | Volume: 16 | Issue: 3 | Page No.: 88-97
DOI: 10.3923/jas.2016.88.97
Bayesian Study Using MCMC of Gompertz Distribution Based on Interval Censored Data with Three Loss Functions
Al Omari Mohammed Ahmed

Abstract:
Interval censored data consist of upper and lower bounds of failure time when the event cannot be observed directly but can only be determined between interval inspection times. The analyzing interval censored data has been developed because it is very common of the medicine and reliability field. The study describes estimation of the Bayesian study using Markov Chain Mote Carlo of the Gompertz distribution under interval censored data, where the full conditional distributions for the parameters, survival function and hazard function are obtained via Metropolis- Hastings algorithm with three loss functions, the Square Error loss function, the Linear Exponential loss function and General Entropy loss function. The methods are compared to maximum likelihood estimation with respect to the Mean Square Error (MSE) and absolute bias to determine the best estimating of the scale and shape parameters, survival function and hazard function of the Gompertz distribution.
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How to cite this article:

Al Omari Mohammed Ahmed , 2016. Bayesian Study Using MCMC of Gompertz Distribution Based on Interval Censored Data with Three Loss Functions. Journal of Applied Sciences, 16: 88-97.

DOI: 10.3923/jas.2016.88.97

URL: https://scialert.net/abstract/?doi=jas.2016.88.97

 
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