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

Deepesh Bhati | Zendy; Subrata Chakraborty | Zendy; Snober Gowhar Lateef | Zendy

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

Author(s) -

Deepesh Bhati,

Subrata Chakraborty,

Snober Gowhar Lateef

Publication year - 2020

Publication title -

filomat

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 0.449

H-Index - 34

eISSN - 2406-0933

pISSN - 0354-5180

DOI - 10.2298/fil2008559b

Subject(s) - mathematics , skew , maximum likelihood , monte carlo method , count data , statistics , distribution (mathematics) , probability distribution , computer science , mathematical analysis , telecommunications , poisson distribution

In this paper, an alternative discrete probability model, namely the 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 the 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 datasets.

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