Showing papers on "Kumaraswamy distribution published in 2012"

The Kumaraswamy Gumbel distribution

Abstract: The Gumbel distribution is perhaps the most widely applied statistical distribution for problems in engineering. We propose a generalization—referred to as the Kumaraswamy Gumbel distribution—and provide a comprehensive treatment of its structural properties. We obtain the analytical shapes of the density and hazard rate functions. We calculate explicit expressions for the moments and generating function. The variation of the skewness and kurtosis measures is examined and the asymptotic distribution of the extreme values is investigated. Explicit expressions are also derived for the moments of order statistics. The methods of maximum likelihood and parametric bootstrap and a Bayesian procedure are proposed for estimating the model parameters. We obtain the expected information matrix. An application of the new model to a real dataset illustrates the potentiality of the proposed model. Two bivariate generalizations of the model are proposed.

The Kumaraswamy-Inverse Weibull Distribution

Abstract: In this paper we have proposed a new four parameter Inverse Weibull distribution that is based upon the cumulative distribution function of Kumaraswamy (1980) distribution. The distributional properties of the proposed distribution have been studied. Special cases of the proposed distribution have also been explored.

The Kumaraswamy–Inverse Weibull Distribution

Abstract: In this paper we have proposed a new four parameter Inverse Weibull distribution that is based upon the cumulative distribution function of Kumaraswamy (1980) distribution. The distributional properties of the proposed distribution have been studied. Special cases of the proposed distribution have also been explored.

Bayesian estimations in the Kumaraswamy distribution under progressively type II censoring data

Abstract: This paper seeks to focus on the study and Bayesian and non-Bayesian estimators for the shape parameter, reliability and failure rate functions of the Kumaraswamy distribution in the cases of progressively type II censored samples. Maximum likelihood estimation and Bayes estimation, reliability and failure rate functions are obtained using symmetric and asymmetric loss functions. Comparisons are made between these estimators using Monte Carlo simulation study. With prior information on the parameter of the Kumaraswamy distribution, Bayes approach under squared error loss function in the reliability function has been suggested based on the pervious observations, this approach can be used for both progressively type II censorings. The study is useful for researchers and practitioners in reliability theory and quality also for scientists in physics and chemistry special hydrological literatare, where Kumaraswamy distribution is widely used.

The McDonald extended distribution: properties and applications

Abstract: We study a five-parameter lifetime distribution called the McDonald extended exponential model to generalize the exponential, generalized exponential, Kumaraswamy exponential and beta exponential distributions, among others. We obtain explicit expressions for the moments and incomplete moments, quantile and generating functions, mean deviations, Bonferroni and Lorenz curves and Gini concentration index. The method of maximum likelihood and a Bayesian procedure are adopted for estimating the model parameters. The applicability of the new model is illustrated by means of a real data set.

Short - Term Wave Statistics In the Greek Seas

Abstract: Short-term analysis of wind waves is often based on the assumption that the sea surface elevation is a stationary and Gaussian process. In this work, measured sea surface elevation data obtained from a deep water wave buoy were analyzed. The work focuses in obtaining the best fit for normalized wave height data using Weibull, Rayleigh and Kumaraswamy distributions. For each sea-state, down-crossing wave heights were identified and the aforementioned theoretical distributions were fitted and assessed. The fit of the Kumaraswamy distribution to the wave height data was found to be much better than that of Weibull and Rayleigh distributions.

On The Generalized Kumaraswamy Distribution

Abstract: This Thesis focuses on the Kumaraswamy-Gumbel minimum distribution as a special distribution from the class of Kw-G distributions, also properties and parameter estimation methods of the Kumaraswamy - Gumbel minimum distribution are studied.