Main Article Content

Abstract

As we mentioned in our previous works, sometimes in real life cases, it is very difficult to obtain samples from a continuous distribution. The observed values are generally discrete due to the fact that they are not measured in continuum. In some cases, it may be possible to measure the observations via a continuous scale, however, they may be recorded in a manner in which a discrete model seems more suitable. Consequently, the discrete models are appearing quite frequently in applied fields and have attracted the attention of many researchers.



Characterizations of distributions are important to many researchers in the applied fields. An investigator will be vitally interested to know if their model fits the requirements of a particular distribution. To this end, one will depend on the characterizations of this distribution which provide conditions under which the underlying distribution is indeed that particular distribution. Here, we present certain characterizations of 14 recently introduced discrete distributions.

Keywords

Keyword1 keyword2

Article Details

How to Cite
Hamedani, G., & Roshani, A. (2022). Characterizations of Fourteen (2021-2022) Proposed Discrete Distributions. Pakistan Journal of Statistics and Operation Research, 18(4), 789-816. https://doi.org/10.18187/pjsor.v18i4.4048

References

  1. Eidous, O.M. and Abu-Shareefa, R., (2020). New approximations for standard normal distribution function. Communications in Statistics-Theory and Methods, 49(6), 1357-1374. DOI: https://doi.org/10.1080/03610926.2018.1563166
  2. Lin, J. T. (1990). A simpler logistic approximation to the normal tail probability and its inverse. Applied Statistics, 39(2), 255–257. DOI: https://doi.org/10.2307/2347764
  3. Zogheib, B., and M. Hlynka. (2009). Approximations of the standard normal distribution. University of Windsor, Dept. of Mathematics and Statistics, on-line text.
  4. Tocher, K. D. (1963). The art of simulation. London: English Universities Press.
  5. Ordaz, M. (1991). A simple approximation to the Gaussian distribution. Structural Safety, 9(4), 315–318. DOI: https://doi.org/10.1016/0167-4730(91)90052-B
  6. Hart, R. G. (1957). A formula for the approximation of the normal distribution function. Mathematical Tables and Other Aids to Computation, 11(60):265. DOI: https://doi.org/10.2307/2001947