On the discrete analog of gamma-Lomax distribution: properties and applications

TL;DR

This paper introduces a discrete gamma-Lomax distribution to model industrial strike data, demonstrating its effectiveness over existing models through empirical fitting and property analysis.

Contribution

The paper proposes a new discrete gamma-Lomax distribution, explores its properties, and applies it to real strike data, showing its usefulness in industrial risk modeling.

Findings

The discrete gamma-Lomax distribution fits strike data well.

It outperforms the discrete generalized Pareto distribution in modeling strikes.

The distribution's properties support its application in industrial risk analysis.

Abstract

This article represents how certain types of blockades in any industrial (heavy industries) production, in particular, industrial strikes can be modeled with the proposed discrete probabilistic distribution as a baseline distribution. We considered the number of outbreaks of strikes in the coal mining industry, the vehicle manufacturing industry, and the transpose industry in the UK obtained from Consul (1989). We fitted those data sets with the proposed discrete gamma-Lomax distribution and compared the fit with the discrete generalized Pareto distribution (Consul, 1989). For this purpose, we explore the basic properties of the discrete gamma-Lomax distribution including but not limited to: cumulative distribution, survival, probability mass, quantile and hazard functions, genesis and rth-order moments; consider maximum likelihood estimation under the normal set up as well as under the censored data set scenario. It is observed that the newly proposed model can be useful to describe strikes arising from various types of industries.