EPANECHNIKOV-WEIBULL DISTRIBUTION

The idea of using kernel functions combined with distributions to propose new distributions is recently used to suggest new continuous distributions. This article combined Epanechnikov kernel function with the Weibull distribution to produce the Epanechnikov-Weibull distribution (EWD). We have presented some properties of EWD, like the moments, MLEs, reliability analysis functions, Re'nyi entropy and the quantile function. We estimate the model parameters using the maximum likelihood method. A simulation study is conducted to calculate the MLE in terms of biases, mean square errors and mean relative, it shows that the estimates are consistent. Two real data sets applications reveal that EWD is more flexible than the Weibull distribution.