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A study of moments and likelihood estimators of the odd Weibull distribution
Affiliation:1. Computer Vision Centre, Universidad Autonoma de Barcelona, Spain;2. Institute for Global Food Security, Queens University Belfast, UK;3. Institute of Electronics, Communications and Information Technology, Queens University Belfast, UK;1. Indian Institute of Technology Mandi, India;2. University of Wisconsin, Madison, United States
Abstract:The odd Weibull distribution is a three-parameter generalization of the Weibull and the inverse Weibull distributions having rich density and hazard shapes for modeling lifetime data. This paper explored the odd Weibull parameter regions having finite moments and examined the relation to some well-known distributions based on skewness and kurtosis functions. The existence of maximum likelihood estimators have shown with complete data for any sample size. The proof for the uniqueness of these estimators is given only when the absolute value of the second shape parameter is between zero and one. Furthermore, elements of the Fisher information matrix are obtained based on complete data using a single integral representation which have shown to exist for any parameter values. The performance of the odd Weibull distribution over various density and hazard shapes is compared with generalized gamma distribution using two different test statistics. Finally, analysis of two data sets has been performed for illustrative purposes.
Keywords:Fisher information matrix  Generalized gamma distribution  Maximum likelihood estimator  Moments  Odd Weibull distribution
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