A discrete probability model suitable for both symmetric and asymmetric count data

Deppesh Bhati, Subrata Chakraborty, Snober Gowhar Lateef


In this paper, an alternative discrete probability model, namely discrete skew logistic distribution, suitable for both asymmetric and symmetric count data is proposed. Some important properties of the distribution along with the estimation of the parameters are discussed. A detailed Monte Carlo simulation study is carried out to assess the performance of maximum likelihood method and the method of proportion for parameter estimation. Finally, the application of the proposed model is discussed by considering two real life dataset in comparison with other discrete distributions.


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