EPANECHNIKOV-WEIBULL DISTRIBUTION

Abstract

The idea of using kernel functions combined with distributions to propose new distributions has recently been used to suggest new continuous distributions. This article combined the 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, Rényi entropy and the quantile function. We estimated the model parameters using the maximum likelihood method. A simulation study was 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 set applications revealed that EWD is more flexible than the Weibull distribution.