Slash-Weighted Lindley Distribution: Properties, Inference, and Applications

Abstract

The slash-weighted Lindley model is introduced due to the need to obtain a model with more kurtosis than the weighted Lindley distribution. Several expressions for the pdf of this model are given. Its cumulative distribution function is expressed in terms of a generalized hypergeometric function and the incomplete gamma function. Moments and maximum likelihood estimation were studied. A simulation study was carried out to illustrate the good performance of the estimates. Finally, two real applications are included.

An Extension of the Fréchet Distribution and Applications

“…In light of the groundbreaking studies by Rogers and Tukey [21], Andrews et al [22] on slash distribution; multivariate slash models proposed in Gómez et al [23] or Arslan and Genc [24], slash methodology has been proven to be useful to increase the weight of tails of a baseline distribution. See for instance Reyes et al [25], Del Castillo [26], Zörnig [27], Olmos et al [28] for the half-normal and generalized half-normal, Astorga et al [19] for the generalized exponential distribution, Barranco-Chamorro et al [29] for the Rayleigh distribution, Barrios et al [30] for the power half-normal, Gui [31] for the Lindley, and Castillo et al [32] for weighted Lindley, among others. However, in this paper, the slash methodology is applied in such a way, that we get a class of distributions more flexible than Fréchet baseline distribution as for skewness and kurtosis.…”