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Recent developments in applied statistics have given rise to the continuous Bernoulli distribution, a one-parameter distribution with support of [0, 1]. In this paper, we use it for a more general purpose: the creation of a family of distributions. We thus exploit the flexible functionalities of the continuous Bernoulli distribution to enhance the modeling properties of well-referenced distributions. We first focus on the theory of this new family, including the quantiles, expansion of important functions, and moments. Then we exemplify it by considering a special baseline: the Topp–Leone distribution. Thanks to the functional structure of the continuous Bernoulli distribution, we create a new two-parameter distribution with support for [0, 1] that possesses versatile shape capacities. In particular, the corresponding probability density function has left-skewed, N-type and decreasing shapes, and the corresponding hazard rate function has increasing and bathtub shapes, beyond the possibilities of the corresponding functions of the Topp–Leone distribution. Its quantile and moment properties are also examined. We then use our modified Topp–Leone distribution from a statistical perspective. The two parameters are supposed to be unknown and then estimated from proportional-type data with the maximum likelihood method. Two different data sets are considered, and reveal that the modified Topp–Leone distribution can fit them better than popular rival distributions, including the unit-Weibull, unit-Gompertz, and log-weighted exponential distributions. It also outperforms the Topp–Leone and continuous Bernoulli distributions.
Czasopismo
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Tom
Numer
Strony
103-124
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autor
- Department of Statistics, University of Benin, Benin City, Nigeria, oponef@dsust.edu.ng
- Department of Statistics, Delta State University of Science and Technology, Ozoro, Nigeria
autor
- Department of Mathematics, LMNO, University of Caen, 14032 Caen, France
Bibliografia
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- Altun, E. The log-weighted exponential regression model: alternative to the beta regression model. Communications in Statistics - Theory and Methods 50, 10 (2021), 2306–2321.
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- Chesneau, C. A note on an extreme left skewed unit distribution: Theory, modelling and data fitting. Open Statistics 2, 1 (2021), 1–23.
- Chesneau, C., and Opone, F. The power continuous Bernoulli distributions: Theory and applications. Reliability: Theory & Applications 17, 4(71) (2022), 232–248.
- Chesneau, C., Opone, F. C., and Ubaka, N. O. Theory and applications of the transmuted continuous Bernoulli distribution. Earthline Journal of Mathematical Sciences 10, 2 (2022), 385–407.
- Van Dorp, J. R., and Kotz, S. Modeling income distributions using elevated distributions on a bounded domain. In Distribution Models Theory (Singapure, 2006), R. Herrerías Pleguezuelo, J. Callejón Céspedes and J. M. Herrerías Velasco, Eds., World Scientific Publishing Co Pte Ltd., pp. 1–25.
- Eugene, N., Lee, C., and Famoye, F. Beta-normal distribution and its applications. Communications in Statistics – Theory and Methods 31, 4 (2002), 497–512.
- Genc, A. İ. Moments of order statistics of Topp–Leone distribution. Statistical Papers 53 (2012), 117–131.
- Ghitany, M. E., Kotz, S., and Xie, M. On some reliability measures and their stochastic orderings for the Topp-Leone distribution. Journal of Applied Statistics 32, 7 (2005), 715–722.
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- Hussain, M. A., Tahir, M. H., and Cordeiro, G. M. A new Kumaraswamy generalized family of distributions: Properties and applications. Mathematica Slovaca 70, 6 (2020), 1491–1510.
- Korkmaz, M. Ç., and Chesneau, C. On the unit Burr-XII distribution with the quantile regression modeling and applications. Computational and Applied Mathematics 40 (2021), 29.
- Korkmaz, M. Ç., Leiva, V., and Martin-Barreiro, C. The continuous Bernoulli distribution: Mathematical characterization, fractile regression, computational simulations, and applications. Fractal and Fractional 7, 5 (2023), 386.
- Loaiza-Ganem, G., and Cunningham, J. P. The continuous Bernoulli: fixing a pervasive error in variational autoencoders. Advances in Neural Information Processing Systems 32 (2019), 13266–13276.
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- Opone, F. C., Akata, I. U., and Altun, E. The Marshall-Olkin extended unit-Gompertz distribution: its properties, regression model and applications. Statistica 82, 2 (2022), 97–118.
- Opone, F. C., Ekhosuehi, N., and Omosigho, S. E. Topp-Leone power Lindley distribution(Tlpld): its properties and application. Sankhya A 84, 2 (2022), 597–608.
- Opone, F. C, and Iwerumor, B. A new Marshall-Olkin extended family of distributions with bounded support. Gazi University Journal of Science 34, 3 (2021), 899–914.
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