Skip to content
Research Article Open access CC BY 4.0

A Finite Mixture of Convex Combination of Probability Models: Properties and Application

K. M. Sakthivel, G. Vidhya

Asian Journal of Probability and Statistics · pp. 24–41 · Published 27 Jun 2023

10.9734/ajpas/2023/v23i2500

Abstract

In this paper, a new continuous probability distribution is developed by using a mixture of exponential and Rayleigh distributions for modeling lifetime data. It has been developed to increase flexibility and shows it can perform better than the existing mixture distributions. The forms of the probability density function and cumulative distribution function along with statistical properties such as moments, incomplete moments, survival function, hazard function, mean residual life, stochastic ordering, order statistics, and stress strength reliability of the proposed distribution are explained. We also obtained the Bonferroni index and Lorenz curve of the proposed distribution. The parameters of the proposed distribution are estimated using the maximum likelihood technique. Finally, data analysis is performed using real-time data to illustrate the suitability of the proposed distribution.

Lifetime distribution hazard function mean residual life function order statistic parameter estimation

References (39)

  1. 1 Mixture models : inference and applications to clustering
  2. 2 Statistical Analysis of Finite Mixture Distributions. [DOI]
  3. 3 Finite Mixture and Markov Switching Models [DOI]
  4. 4 Fiducial Distributions and Bayes' Theorem [DOI]
  5. 5 Lindley distribution and its application [DOI]
  6. 6 Statistical Methods for Survival Data Analysis [DOI]
  7. 7 Inflated beta distributions [DOI]
  8. 8 Mixture Model-Based Classification [DOI]
  9. 9 Medical Applications of Finite Mixture Models [DOI]
  10. 10 The Gompertz-G family of distributions [DOI]
  11. 11 Pranav distribution with properties and its applications [DOI]
  12. 12 Finite Mixture Distributions [DOI]
  13. 13 Sujatha Distribution and its Applications [DOI]
  14. 14 Shanker Distribution and Its Applications
  15. 15 Akash Distribution and Its Applications
  16. 16 Ishita Distribution and Its Applications [DOI]
  17. 17 Aradhana Distribution and Its Applications
  18. 18 Alpha-Power Exponentiated Inverse Rayleigh distribution and its applications to real and simulated data [DOI]
  19. 19 A new generalized rayleigh distribution with analysis to big data of an online community [DOI]
  20. 20 Rama Distribution and Its Application
  21. 21 The discrete power-Ailamujia distribution: properties, inference, and applications [DOI]
  22. 22 A Novel Generator of Continuous Probability Distributions for the Asymmetric Left-skewed Bimodal Real-life Data with Properties and Copulas [DOI]
  23. 23 On a Modified Weighted Exponential Distribution with Applications [DOI]
  24. 24 Shukla Distribution and its Application [DOI]
  25. 25 Finite Mixture of Skewed Distributions [DOI]
  26. 26 Amarendra Distribution and Its Applications
  27. 27 Darna Distribution: Properties and Application [DOI]
  28. 28 Bonferroni and Gini indices for various parametric families of distributions [DOI]
  29. 29 Janardan Distribution and its Application to Waiting Times Data [DOI]
  30. 30 Ram Awadh distribution with properties and applications [DOI]
  31. 31 A novel family of lifetime distribution with applications to real and simulated data [DOI]
  32. 32 Alzoubi Distribution: Properties and Applications [DOI]
  33. 33 A new two-parameter distribution: properties and applications [DOI]
  34. 34 Exponentiated Gompertz Exponential (Egoe) Distribution: Derivation, Properties and Applications
  35. 35 A New Sushila Distribution: Properties and Applications [DOI]
  36. 36 Om Distribution With Properties And Applications [DOI]
  37. 37 Rama-Kamlesh distribution with properties and Its Applications
  38. 38 Mixture Models: Inference and Applications to Clustering. [DOI]
  39. 39 Statistical Methods for Survival Data Analysis [DOI]

Cited by 2

An Adaptable Gamma (2,1)–Gamma–G Lifetime Model with Hybrid Classical–Fuzzy–Deep Learning Approximation

V. Shakila, L. Sujatha, B. Sivakumar · International Journal of Fuzzy Systems · 2026

Showing 1 of 2 known citations — external sources report more than can currently be individually listed.

Related research

Article metrics

Real usage data collected on this platform.

71

Page views

0

PDF downloads

30

Outbound clicks

2

Citations

Views over time

Views by country

Approximate, from request IP at view time — not citizenship or institution. Countries with fewer than 5 views are grouped as "Other".

Traffic sources

Referring site, by host.

Views and downloads exclude known bots/crawlers. Citations combines this platform's own DOI-resolved index with each external source's own reported total — see Cited by above for individually listed citing works. Last refreshed 0 seconds ago.