Research Article
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Exponentiated generalized Ramos-Louzada distribution with properties and applications

Year 2024, Volume: 73 Issue: 1, 76 - 103, 16.03.2024
https://doi.org/10.31801/cfsuasmas.1147449

Abstract

In this paper, we propose a new generalization of Ramos-Louzada (RL) distribution based on two additional shape parameters. Along with the genesis of its distributional form, the derivation of cumulative density function (cdf), survival and hazard rate functions, the quantile function (qf), moments, moment generating function (mgf), Shannon and Renyi entropies, order statistics and a linear representation of the proposed distribution are inspected. Several estimation methods of the model parameters are discussed throughout two comprehensive simulation studies conducted to compare its performance against some lifetime distributions. Application of a real dataset is presented to illustrate the potentiality of this distribution in line with the simulation studies.

References

  • Akaike, H., Information theory and an extension of the maximum likelihood principle, In B.N. Petrov & F. Csaki (Eds.), Proc. 2nd Int. Symp. Information Theory, Budapest: Akademiai Kiado, (1973), 267-281.
  • Akaike, H., A new look at the statistical model identification, IEEE Transaction on Automatic Control, 19 (1974), 716-723. http://dx.doi.org/10.1109/TAC.1974.1100705
  • Al-Mofleh, H., Afifty, A., Ibrahim, N. A., A new extended two-parameter distribution: Properties, estimation methods and applications in medicine and geology, Mathematics, 8 (2020), 1578. http://dx.doi.org/10.3390/math8091578
  • Alzaatreh, A., Lee, C., Famoye, F., A new method for generating families of continuous distributions, METRON, 71 (2013), 63-79. http://dx.doi.org/10.1007/s40300-013-0007-y
  • Arnold, B. C., Balakrishnan, A. N., Nagaraja, H. N., A First Course in Order Statistics, New York: Wiley-Interscience, 1992.
  • Bozdogan, H., Model selection and Akaike’s information criterion (AIC): The general theory and its analytical extensions, Psychometrika, 52 (1987), 345-370. http://dx.doi.org/10.1007/BF02294361
  • Corderio, G. M., Ortega, E. M. M., Cunha, D. C. C., The exponentiated generalized class of distributions, Journal of Data Science, 11 (2013), 1-27. http://dx.doi.org/10.6339/JDS.2013.11(1).1086
  • Corderio, G. M., Lemonte, A. J., The exponentiated generalized Birnbaum-Sanders distribution, Applied Mathematics and Computation, 247 (2014), 762-779. http://dx.doi.org/10.1016/j.amc.2014.09.054
  • Cramer, H., On the composition of elementary errors, Scandinavian Actuarial Journal, 1 (1928), 13-74. http://dx.doi.org/10.1080/03461238.1928.10416862
  • Efron, B., Tibshirani, R. J., An Introduction to the Bootstrap, New York: Chapman & Hall.
  • Gupta, R. D., Kundu, D., Exponentiated exponential family: An alternative to gamma and Weibull distributions, Biometrical Journal, 43 (2001), 117-130. http://dx.doi.org/10.1002/1521-4036(200102)43:1<117::AID-BIMJ117>3.0.CO;2-R
  • Hannan, E. J., Quinn, B. G., The determination of the order of an autoregression, Journal of the Royal Statistical Society, Series B, 41 (1979), 190-195. http://www.jstor.org/stable/2985032
  • Hörmann, W., Leydold, J., Derflinger, G., Automatic Nonuniform Random Variate Generation, Springer-Verlag, Berlin Heidelberg, 2004.
  • Hurvich, C. M., Tsai, C. L., Regression and time series model selection in small samples, Biometrika, 76 (1989), 297-307. http://dx.doi.org/10.1093/biomet/76.2.297
  • Kenney, J. F., Keeping, E. S., Mathematics of Statistics, Pt. 1, 3rd ed. Princeton, NJ: Van Nostrand, 1962.
  • Kolmogorov, A., Sulla determinazione empirica di una legge di distribuzione, Giornale della Istituto Italiano degli Attuari, 4 (1933), 83-91.
  • Kuiper, N. H., Tests concerning random points on a circle, Proceedings of the Koninklijke Nederlandse Akademie van Wetenschappen Series A, 63 (1960), 38-47. http://dx.doi.org/10.1016/S1385-7258(60)50006-0
  • Lee, E. T., Wang, J. W., Statistical Methods for Survival Data Analysis, Wiley, New York, 2003.
  • Lindley, D. V., Fiducial distributions and Bayes’ theorem, Journal of the Royal Statistical Society Series B, 20 (1958), 102-107. http://www.jstor.org/stable/2983909
  • MacDonald, P. D. M., Comment on “An estimation procedure for mixtures of distributions” by Choi and Bulgren, Journal of the Royal Statistical Society Series B, 33 (1971), 326-329. https://www.jstor.org/stable/2985013
  • Marshall, A. W., Olkin, I., A new method for adding a parameter to a family of distributions with application to the exponential and Weibull families, Biometrika, 84 (1997), 641-652. http://dx.doi.org/10.1093/biomet/92.2.505
  • Moors, J. J. A., A quantile alternative for kurtosis, Journal of the Royal Statistical Society Series D (The Statistician), 37(1988), 25-32. https://doi.org/10.2307/2348376
  • Nadarajah, S., Bakouch, H. S., Tahmasbi, R., A generalized Lindley distribution, Sankhya B, 73 (2011), 331-359. https://doi.org/10.1007/s13571-011-0025-9
  • Ramos, R. L., Louzada, F., A distribution for instantaneous failures, Stats, 2 (2019), 247-258. https://doi.org/10.3390/stats2020019
  • Rayleigh, L., On the stability, or instability, of certain fluid motions, Proceedings of the London Mathematical Society, 11(1879), 57-72. https://doi.org/10.1112/plms/s1-11.1.57
  • Renyi, A., On measures of entropy and information, Proceedings of the Fourth Berkeley Symposium on Mathematical Statistics and Probability, 1 (1961), 547-561.
  • Rioul, O., This is IT: A Primer on Shannon's entropy and information. In: Duplantier, B., Rivasseau, V. (eds) Information Theory. Progress in Mathematical Physics, 78(2021).https://doi.org/10.1007/978-3-030-81480-9_2
  • Sanku, D., Enayetur, R., Saikat, M., Statistical properties and different methods of estimation of transmuted Rayleigh distribution, Revista Colombiana de Estadistica, 40 (2017), 165-203. https://doi.org/10.15446/rce.v40n1.56153
  • Schwarz, G., Estimating the dimension of a model, Annals of Statistics, 6 (1978), 461-464. https://doi.org/10.1214/aos/1176344136
  • Shannon, C. E., A mathematical theory of communication, Bell System Technical Journal, 27 (1948), 379-432. https://doi.org/10.1002/j.1538-7305.1948.tb01338.x
  • Smirnov, N., Table for estimating the goodness of fit of empirical distributions, Annals of Mathematical Statistics, 19 (1948), 279-281. https://doi.org/10.1214/aoms/1177730256
  • Sohn, B. Y., Kim, G. B., Detection of outliers in weighted least squares regression, Korean Journal of Computational & Applied Mathematics, 4 (1997), 441-452. https://doi.org/10.1007/BF03014491
  • Swain, J. J., Venkatraman, S., Wilson, J. R., Least-squares estimation of distribution functions in Johnson’s translation system, Journal of Statistical Computation and Simulation, 29 (1988), 271-297. https://doi.org/10.1080/00949658808811068
  • Walther, B. A., Moore, J. J., The concepts of bias, precision and accuracy, and their use in testing the performance of species richness estimators, with a literature review of estimator performance, Ecography, 28 (2005), 815-829. https://doi.org/10.1111/j.2005.0906-7590.04112.x
  • Watson, G. S., Goodness-of-fit tests on a circle, Biometrika, 48 (1961), 109-114. https://doi.org/10.2307/2333135
Year 2024, Volume: 73 Issue: 1, 76 - 103, 16.03.2024
https://doi.org/10.31801/cfsuasmas.1147449

Abstract

References

  • Akaike, H., Information theory and an extension of the maximum likelihood principle, In B.N. Petrov & F. Csaki (Eds.), Proc. 2nd Int. Symp. Information Theory, Budapest: Akademiai Kiado, (1973), 267-281.
  • Akaike, H., A new look at the statistical model identification, IEEE Transaction on Automatic Control, 19 (1974), 716-723. http://dx.doi.org/10.1109/TAC.1974.1100705
  • Al-Mofleh, H., Afifty, A., Ibrahim, N. A., A new extended two-parameter distribution: Properties, estimation methods and applications in medicine and geology, Mathematics, 8 (2020), 1578. http://dx.doi.org/10.3390/math8091578
  • Alzaatreh, A., Lee, C., Famoye, F., A new method for generating families of continuous distributions, METRON, 71 (2013), 63-79. http://dx.doi.org/10.1007/s40300-013-0007-y
  • Arnold, B. C., Balakrishnan, A. N., Nagaraja, H. N., A First Course in Order Statistics, New York: Wiley-Interscience, 1992.
  • Bozdogan, H., Model selection and Akaike’s information criterion (AIC): The general theory and its analytical extensions, Psychometrika, 52 (1987), 345-370. http://dx.doi.org/10.1007/BF02294361
  • Corderio, G. M., Ortega, E. M. M., Cunha, D. C. C., The exponentiated generalized class of distributions, Journal of Data Science, 11 (2013), 1-27. http://dx.doi.org/10.6339/JDS.2013.11(1).1086
  • Corderio, G. M., Lemonte, A. J., The exponentiated generalized Birnbaum-Sanders distribution, Applied Mathematics and Computation, 247 (2014), 762-779. http://dx.doi.org/10.1016/j.amc.2014.09.054
  • Cramer, H., On the composition of elementary errors, Scandinavian Actuarial Journal, 1 (1928), 13-74. http://dx.doi.org/10.1080/03461238.1928.10416862
  • Efron, B., Tibshirani, R. J., An Introduction to the Bootstrap, New York: Chapman & Hall.
  • Gupta, R. D., Kundu, D., Exponentiated exponential family: An alternative to gamma and Weibull distributions, Biometrical Journal, 43 (2001), 117-130. http://dx.doi.org/10.1002/1521-4036(200102)43:1<117::AID-BIMJ117>3.0.CO;2-R
  • Hannan, E. J., Quinn, B. G., The determination of the order of an autoregression, Journal of the Royal Statistical Society, Series B, 41 (1979), 190-195. http://www.jstor.org/stable/2985032
  • Hörmann, W., Leydold, J., Derflinger, G., Automatic Nonuniform Random Variate Generation, Springer-Verlag, Berlin Heidelberg, 2004.
  • Hurvich, C. M., Tsai, C. L., Regression and time series model selection in small samples, Biometrika, 76 (1989), 297-307. http://dx.doi.org/10.1093/biomet/76.2.297
  • Kenney, J. F., Keeping, E. S., Mathematics of Statistics, Pt. 1, 3rd ed. Princeton, NJ: Van Nostrand, 1962.
  • Kolmogorov, A., Sulla determinazione empirica di una legge di distribuzione, Giornale della Istituto Italiano degli Attuari, 4 (1933), 83-91.
  • Kuiper, N. H., Tests concerning random points on a circle, Proceedings of the Koninklijke Nederlandse Akademie van Wetenschappen Series A, 63 (1960), 38-47. http://dx.doi.org/10.1016/S1385-7258(60)50006-0
  • Lee, E. T., Wang, J. W., Statistical Methods for Survival Data Analysis, Wiley, New York, 2003.
  • Lindley, D. V., Fiducial distributions and Bayes’ theorem, Journal of the Royal Statistical Society Series B, 20 (1958), 102-107. http://www.jstor.org/stable/2983909
  • MacDonald, P. D. M., Comment on “An estimation procedure for mixtures of distributions” by Choi and Bulgren, Journal of the Royal Statistical Society Series B, 33 (1971), 326-329. https://www.jstor.org/stable/2985013
  • Marshall, A. W., Olkin, I., A new method for adding a parameter to a family of distributions with application to the exponential and Weibull families, Biometrika, 84 (1997), 641-652. http://dx.doi.org/10.1093/biomet/92.2.505
  • Moors, J. J. A., A quantile alternative for kurtosis, Journal of the Royal Statistical Society Series D (The Statistician), 37(1988), 25-32. https://doi.org/10.2307/2348376
  • Nadarajah, S., Bakouch, H. S., Tahmasbi, R., A generalized Lindley distribution, Sankhya B, 73 (2011), 331-359. https://doi.org/10.1007/s13571-011-0025-9
  • Ramos, R. L., Louzada, F., A distribution for instantaneous failures, Stats, 2 (2019), 247-258. https://doi.org/10.3390/stats2020019
  • Rayleigh, L., On the stability, or instability, of certain fluid motions, Proceedings of the London Mathematical Society, 11(1879), 57-72. https://doi.org/10.1112/plms/s1-11.1.57
  • Renyi, A., On measures of entropy and information, Proceedings of the Fourth Berkeley Symposium on Mathematical Statistics and Probability, 1 (1961), 547-561.
  • Rioul, O., This is IT: A Primer on Shannon's entropy and information. In: Duplantier, B., Rivasseau, V. (eds) Information Theory. Progress in Mathematical Physics, 78(2021).https://doi.org/10.1007/978-3-030-81480-9_2
  • Sanku, D., Enayetur, R., Saikat, M., Statistical properties and different methods of estimation of transmuted Rayleigh distribution, Revista Colombiana de Estadistica, 40 (2017), 165-203. https://doi.org/10.15446/rce.v40n1.56153
  • Schwarz, G., Estimating the dimension of a model, Annals of Statistics, 6 (1978), 461-464. https://doi.org/10.1214/aos/1176344136
  • Shannon, C. E., A mathematical theory of communication, Bell System Technical Journal, 27 (1948), 379-432. https://doi.org/10.1002/j.1538-7305.1948.tb01338.x
  • Smirnov, N., Table for estimating the goodness of fit of empirical distributions, Annals of Mathematical Statistics, 19 (1948), 279-281. https://doi.org/10.1214/aoms/1177730256
  • Sohn, B. Y., Kim, G. B., Detection of outliers in weighted least squares regression, Korean Journal of Computational & Applied Mathematics, 4 (1997), 441-452. https://doi.org/10.1007/BF03014491
  • Swain, J. J., Venkatraman, S., Wilson, J. R., Least-squares estimation of distribution functions in Johnson’s translation system, Journal of Statistical Computation and Simulation, 29 (1988), 271-297. https://doi.org/10.1080/00949658808811068
  • Walther, B. A., Moore, J. J., The concepts of bias, precision and accuracy, and their use in testing the performance of species richness estimators, with a literature review of estimator performance, Ecography, 28 (2005), 815-829. https://doi.org/10.1111/j.2005.0906-7590.04112.x
  • Watson, G. S., Goodness-of-fit tests on a circle, Biometrika, 48 (1961), 109-114. https://doi.org/10.2307/2333135
There are 35 citations in total.

Details

Primary Language English
Subjects Statistics
Journal Section Research Articles
Authors

Yasin Altinisik 0000-0001-9375-2276

Emel Çankaya 0000-0002-2892-2520

Publication Date March 16, 2024
Submission Date July 23, 2022
Acceptance Date October 6, 2023
Published in Issue Year 2024 Volume: 73 Issue: 1

Cite

APA Altinisik, Y., & Çankaya, E. (2024). Exponentiated generalized Ramos-Louzada distribution with properties and applications. Communications Faculty of Sciences University of Ankara Series A1 Mathematics and Statistics, 73(1), 76-103. https://doi.org/10.31801/cfsuasmas.1147449
AMA Altinisik Y, Çankaya E. Exponentiated generalized Ramos-Louzada distribution with properties and applications. Commun. Fac. Sci. Univ. Ank. Ser. A1 Math. Stat. March 2024;73(1):76-103. doi:10.31801/cfsuasmas.1147449
Chicago Altinisik, Yasin, and Emel Çankaya. “Exponentiated Generalized Ramos-Louzada Distribution With Properties and Applications”. Communications Faculty of Sciences University of Ankara Series A1 Mathematics and Statistics 73, no. 1 (March 2024): 76-103. https://doi.org/10.31801/cfsuasmas.1147449.
EndNote Altinisik Y, Çankaya E (March 1, 2024) Exponentiated generalized Ramos-Louzada distribution with properties and applications. Communications Faculty of Sciences University of Ankara Series A1 Mathematics and Statistics 73 1 76–103.
IEEE Y. Altinisik and E. Çankaya, “Exponentiated generalized Ramos-Louzada distribution with properties and applications”, Commun. Fac. Sci. Univ. Ank. Ser. A1 Math. Stat., vol. 73, no. 1, pp. 76–103, 2024, doi: 10.31801/cfsuasmas.1147449.
ISNAD Altinisik, Yasin - Çankaya, Emel. “Exponentiated Generalized Ramos-Louzada Distribution With Properties and Applications”. Communications Faculty of Sciences University of Ankara Series A1 Mathematics and Statistics 73/1 (March 2024), 76-103. https://doi.org/10.31801/cfsuasmas.1147449.
JAMA Altinisik Y, Çankaya E. Exponentiated generalized Ramos-Louzada distribution with properties and applications. Commun. Fac. Sci. Univ. Ank. Ser. A1 Math. Stat. 2024;73:76–103.
MLA Altinisik, Yasin and Emel Çankaya. “Exponentiated Generalized Ramos-Louzada Distribution With Properties and Applications”. Communications Faculty of Sciences University of Ankara Series A1 Mathematics and Statistics, vol. 73, no. 1, 2024, pp. 76-103, doi:10.31801/cfsuasmas.1147449.
Vancouver Altinisik Y, Çankaya E. Exponentiated generalized Ramos-Louzada distribution with properties and applications. Commun. Fac. Sci. Univ. Ank. Ser. A1 Math. Stat. 2024;73(1):76-103.

Communications Faculty of Sciences University of Ankara Series A1 Mathematics and Statistics.

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