Application of Mixture of Weibull and Pareto (IV) Distribution to Health and Environmental Data

Weibull and Pareto distributions are widely used in several areas, including lifetime data modelling and reliability analysis. In real-life practice, these distributions may not capture the various distributional properties of certain datasets. The use of finite mixture models enhanced the performances of these distributions in adaptability and accuracy. This study focused on the Mixture Weibull Pareto (IV) distribution proposed by [1], which has been used in modelling insurance claims, and it showed superior performance as compared with other distributions. The current study applied this distribution to health and environmental datasets. The result showed that the Mixture Weibull Pareto (IV) distribution performed better than other distributions, using Akaike Information Criterion (AIC), Bayesian Information Criterion (BIC) and Kolmogorov-Smirnov test (KS test) for the significance of the distribution.