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Extended Weibull type distribution and finite mixture of distributions
Authors:Jamal A Al-Saleh  Satish K Agarwal  
Institution:aDepartment of Statistics and Operation Research, Faculty of Science, Kuwait University, P.O. Box 5969, Safat, Kuwait;bDepartment of Mathematics, College of Science, University of Bahrain, P.O. Box 32038, Bahrain
Abstract:An extended form of Weibull distribution is suggested which has two shape parameters (m and δ). Introduction of another shape parameter δ helps to express the extended Weibull distribution not only as an exact form of a mixture of distributions under certain conditions, but also provides extra flexibility to the density function over positive range. The shape of density function of the extended Weibull type distribution for various values of the parameters is shown which may be of some interest to Bayesians. Certain statistical properties such as hazard rate function, mean residual function, rth moment are defined explicitly. The proposed extended Weibull distribution is used to derive an exact form of two, three and k-component mixture of distributions. With the help of a real data set, the usefulness of mixture Weibull type distribution is illustrated by using Markov Chain Monte Carlo (MCMC), Gibbs sampling approach.
Keywords:Bayesian analysis  Extended Weibull distribution  Finite mixture distribution  Gibbs sampling  Kobayashi’  s gamma type function  Markov Chian Monte Carlo
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