Sushila-Geometric distribution, properties, and applications

  • Anis Iranmanesh Department of Mathematics and Statistics, Mashhad Branch, Islamic Azad University, Mashhad, Iran;
  • Sepideh Daghagh Mashhad Branch, Islamic Azad University, Mashhad, Iran.
  • Ehsan Ormoz Department of Mathematics and Computer Sciences, Ma.C., Islamic Azad University, Mashhad, Iran
DOI: https://doi.org/10.19139/soic-2310-5070-1722
Keywords: EM algorithm; Maximum likelihood estimation; Geometric distribution; Sushila distribution.

Abstract

In the present paper, we introduce a compound form of the Sushila distribution which offers a flexible modelfor lifetime data, the so-called Sushila-geometric $(SG)$ distribution, and is obtained by compounding Sushila and geometric distributions. A three-parameter $SG$ distribution is capable of modelling upside-down bathtub, bathtub-shaped, increasing and decreasing hazard rate functions which are widely used in engineering, economy and natural sciences. This new model contains some known distributions such as Lindley, Lindley-Geometric, and Sushila distributions in a special cases as sub-models. Several statistical properties of the $SG$ distribution are derived. Simulation studies are conducted to investigate the performance of the maximum likelihood estimators derived through the EM algorithm. The flexibility of the new model is illustrated in the application of two real data sets.
Published
2025-10-03
How to Cite
Iranmanesh, A., Daghagh, S., & Ormoz, E. (2025). Sushila-Geometric distribution, properties, and applications. Statistics, Optimization & Information Computing. https://doi.org/10.19139/soic-2310-5070-1722
Issue
Online First
Section
Research Articles
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