An α-Monotone Generalized Log-Moyal Distribution with Applications to Environmental Data

Modeling environmental data plays a crucial role in explaining phenomena. In some cases, well-known distributions, e.g., Weibull, inverse and Gumbel cannot model events adequately. Therefore, many authors tried to find new statistical distributions represent phenomena more accurately. this paper, an α-monotone generalized log-Moyal (α-GlogM) distribution is introduced properties such as cumulative function, hazard rate function (hrf), scale-mixture representation, moments are derived. The hrf of the α-GlogM can form variety shapes including bathtub shape. converges half-normal (GHN) GHN distributions. It reduces slash for certain parameter settings. Environmental sets used show implementations also compare its modeling performance with rivals. comparisons carried out using information criteria goodness-of-fit statistics. comparison results that preferable over rivals terms capability.