A discrete probability model suitable for both symmetric and asymmetric count data
Filomat, Tome 34 (2020) no. 8, p. 2559
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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.
Classification :
60E05, 62E15, 62F10
Keywords: Discretization, Asymmetric count data, Skew Logistics Distribution, Generalized Geometric Distribution
Keywords: Discretization, Asymmetric count data, Skew Logistics Distribution, Generalized Geometric Distribution
Deepesh Bhati; Subrata Chakraborty; Snober Gowhar Lateef. A discrete probability model suitable for both symmetric and asymmetric count data. Filomat, Tome 34 (2020) no. 8, p. 2559 . doi: 10.2298/FIL2008559B
@article{10_2298_FIL2008559B,
author = {Deepesh Bhati and Subrata Chakraborty and Snober Gowhar Lateef},
title = {A discrete probability model suitable for both symmetric and asymmetric count data},
journal = {Filomat},
pages = {2559 },
year = {2020},
volume = {34},
number = {8},
doi = {10.2298/FIL2008559B},
language = {en},
url = {http://geodesic.mathdoc.fr/articles/10.2298/FIL2008559B/}
}
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