Abstract
An Exponentiated Exponential Weibull Distribution (EEWD) is proposed. Some statistical properties of the proposed distribution are studied. The Maximum Likelihood method (ML) is applied to estimate the model parameters. The efficiency of the ML estimates of the proposed model is demonstrated using a Monte Carlo simulation study with different samples sizes. Moreover, real data set application is provided to show the flexibility of the proposed model in comparison to some selected distributions.
Highlights
Statistical distributions are of vital importance in fitting data in real phenomena
To evaluate the performance of the MLEs of the Exponential Weibull Distribution (EEWD) obtained in section (5), we provide a Monte Carlo simulation study
To assess the performance of the MLEs a simulation study is conducted under various sample sizes
Summary
Statistical distributions are of vital importance in fitting data in real phenomena. It is widely applied to model and analyze data in different disciplines such as engineering, biology, economics, finance and medical sciences. This method proposed by (Gupta et al, 1998) and named the exponentiated method as the Cumulative Distribution Function (cdf) of any distribution has been raised to a parameter; a new flexible distribution is generated. Different types of generators can be applied to obtain new families of distributions. Let X be a random variable for any continuous distribution, the cdf for the T-X family is given by:
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