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Research Articles

An Alternative Discrete Analogue of the Half-Logistic Distribution Based on Minimization of a Distance between Cumulative Distribution Functions

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References

  • Balakrishnan, N. (1985). Order statistics from the half logistic distribution. Journal of Statistical Computation and Simulation, 20(4), 287–309. https://doi.org/10.1080/00949658508810784
  • Barbiero, A., & Hitaj, A. (2020). A discrete analogue of the half-logistic distribution [Paper presentation]. 2020 International Conference on Decision Aid Sciences and Application (DASA), In (pp. 64–67). https://doi.org/10.1109/DASA51403.2020.9317237
  • Barbiero, A., & Hitaj, A. (2021). A new method for building a discrete analogue to a continuous random variable based on minimization of a distance between distribution functions [Paper presentation]. 2021 International Conference on Data Analytics for Business and Industry (ICDABI), In (pp. 338–341). https://doi.org/10.1109/ICDABI53623.2021.9655904
  • Barbiero, A., & Hitaj, A. (2023). An alternative discrete analogue of the half-logistic distribution. Proceedings of International Mathematical Sciences, 5(2), 14–18. https://doi.org/10.47086/pims.1346708
  • Bolker, B, R Development Core Team (2022). bbmle: Tools for general maximum likelihood estimation [Computer software manual]. Retrieved from https://CRAN.R-project.org/package=bbmle (R package version 1.0.25)
  • Chakraborti, S., Jardim, F., & Epprecht, E. (2019). Higher-order moments using the survival function: The alternative expectation formula. The American Statistician, 73(2), 191–194. https://doi.org/10.1080/00031305.2017.1356374
  • Chakraborty, S., & Gupta, R. D. (2015). Exponentiated geometric distribution: Another generalization of geometric distribution. Communications in Statistics - Theory and Methods, 44(6), 1143–1157. https://doi.org/10.1080/03610926.2012.763090
  • Croissant, Y., Graves, S. (2022). Ecdat: Data sets for econometrics [Computer software manual]. Retrieved from https://CRAN.R-project.org/package=Ecdat (R package version 0.4-2)
  • Dunn, P. K., & Smyth, G. K. (1996). Randomized quantile residuals. Journal of Computational and Graphical Statistics, 5(3), 236–244. https://doi.org/10.2307/1390802
  • Feng, C., Li, L., & Sadeghpour, A. (2020). A comparison of residual diagnosis tools for diagnosing regression models for count data. BMC Medical Research Methodology, 20(1), 175. https://doi.org/10.1186/s12874-020-01055-2
  • Hilbe, J. M. (2016). Count: Functions, data and code for count data [Computer software manual]. Retrieved from https://CRAN.R-project.org/package=COUNT (R package version 1.3.4)
  • Jornsatian, C., & Bodhisuwan, W. (2022). Bayesian inference for negative binomial—Beta exponential distribution and its regression model. Lobachevskii Journal of Mathematics, 43(9), 2501–2514. https://doi.org/10.1134/S1995080222120162
  • Khan, M. A., Khalique, A., & Abouammoh, A. (1989). On estimating parameters in a discrete Weibull distribution. IEEE Transactions on Reliability, 38(3), 348–350. https://doi.org/10.1109/24.44179
  • Klakattawi, H. S., Vinciotti, V., & Yu, K. (2018). A simple and adaptive dispersion regression model for count data. Entropy, 20(2), 142. https://doi.org/10.3390/e20020142
  • Lee, C., Famoye, F., & Alzaatreh, A. Y. (2013). Methods for generating families of univariate continuous distributions in the recent decades. WIREs Computational Statistics, 5(3), 219–238. https://doi.org/10.1002/wics.1255
  • R Core Team (2023). R: A language and environment for statistical computing [Computer software manual]. Vienna, Austria. Retrieved from https://www.R-project.org/
  • Ridout, M. S., & Besbeas, P. (2004). An empirical model for underdispersed count data. Statistical Modelling, 4(1), 77–89. https://doi.org/10.1191/1471082X04st064oa
  • Rubinstein, R. Y., & Kroese, D. P. (2016). Simulation and the Monte Carlo method. John Wiley & Sons.
  • Steutel, F. W., & Van Harn, K. (2003). Infinite divisibility of probability distributions on the real line. CRC Press.

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