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Chris-Jerry Distribution and Its Applications

  • Chrisogonus K. Onyekwere
  • Okechukwu J. Obulezi

Asian Journal of Probability and Statistics, Page 16-30
DOI: 10.9734/ajpas/2022/v20i130480
Published: 17 September 2022

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Abstract


In this paper, a new one-parameter distribution named Chris-Jerry is suggested from two component mixture of Exponential (\(\theta\)) distribution and Gamma(3; \(\theta\)) distribution with mixing proportion \(p=\frac{\theta}{\theta + 2}\) having a flexibility advantage in modeling lifetime data. The statistical properties are discussed and the maximum likelihood estimation procedure is used to obtain the parameter estimate. The Convolution of the product of Pareto random variable with the proposed Chris-Jerry distributed random variable is explored with its marginal density derived. To illustrate the usefulness, three sets of lifetime data are employed and LL, AIC, BIC and K-S statistics are obtained for Exponential, Ishita, Akash, Rama, Pranav, Rani, Lindley, Sujatha, Aradhana, Shanker and XGamma and the Chris-Jerry distributions.


Keywords:
  • Chris-Jerry distribution
  • exponential distribution
  • gamma distribution
  • component mixture
  • heavy-tailed distribution
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How to Cite

Onyekwere, C. K., & Obulezi, O. J. (2022). Chris-Jerry Distribution and Its Applications. Asian Journal of Probability and Statistics, 20(1), 16-30. https://doi.org/10.9734/ajpas/2022/v20i130480
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