Fitting UK strike data using a discrete analogue of gamma-Lomax distribution Indranil Ghosh 1 , Ayman Alzaatreh 2 , GG Hamedani 3 1 University of North Carolina, Wilmington, North Carolina, USA 2 American University of Sharjah, Sharjah, UAE 3 Marquette University, Milwaukee, USA. Corresponding author E-mail address: ghoshi@uncw.edu Abstract This article represents how certain types of blockades in any industrial (heavy in- dustries) 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 haz- ard 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. Key Words: Industrial strike data analysis; Discrete gamma-Lomax distribution; Infi- nite divisibility; Maximum likelihood estimation. 1 arXiv:1802.08951v2 [math.ST] 20 Mar 2020