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Licensed Unlicensed Requires Authentication Published by De Gruyter November 10, 2020

The Reflected-Shifted-Truncated Lindley Distribution with Applications

  • Sanku Dey , Sophia Waymyers and Devendra Kumar ORCID logo EMAIL logo

Abstract

In this paper, a new probability density function with bounded domain is presented. The new distribution arises from the Lindley distribution proposed in 1958. It presents the advantage of not including any special function in its formulation. The new transformed model, called the reflected-shifted-truncated Lindley distribution can be used to model left-skewed data. We provide a comprehensive treatment of general mathematical and statistical properties of this distribution. We estimate the model parameters by maximum likelihood methods based on complete and right-censored data. To assess the performance and consistency of the maximum likelihood estimators, we conduct a simulation study with varying sample sizes. Finally, we use the distribution to model left-skewed survival and failure data from two real data sets. For the real data sets containing complete data and right-censored data, this distribution is superior in its ability to sufficiently model the data as compared to the power Lindley, exponentiated power Lindley, generalized inverse Lindley, generalized weighted Lindley and the well-known Gompertz distributions.

MSC 2010: 60E05; 62F10

Acknowledgements

The authors thank the editor and associate editor of the journal, and the anonymous reviewer for their constructive suggestions which helped us to improve the earlier version of this manuscript.

References

[1] A. Asgharzadeh, H. S. Bakouch, S. Nadarajah and F. Sharafi, A new weighted Lindley distribution with application, Braz. J. Probab. Stat. 30 (2016), no. 1, 1–27. 10.1214/14-BJPS253Search in Google Scholar

[2] S. K. Ashour and M. A. Eltehiwy, Exponentiated power Lindley distribution, J. Adv. Res. 6 (2015), no. 6, 895–905. 10.1016/j.jare.2014.08.005Search in Google Scholar PubMed PubMed Central

[3] H. S. Bakouch, B. M. Al-Zahrani, A. A. Al-Shomrani, V. A. A. Marchi and F. Louzada, An extended Lindley distribution, J. Korean Statist. Soc. 41 (2012), no. 1, 75–85. 10.1016/j.jkss.2011.06.002Search in Google Scholar

[4] W. Barreto-Souza and H. S. Bakouch, A new lifetime model with decreasing failure rate, Statistics 47 (2013), no. 2, 465–476. 10.1080/02331888.2011.595489Search in Google Scholar

[5] K. P. Burnham and D. R. Anderson, Model Selection and Multimodel Inference: A Practical Information-Theoretic Approach, 2nd ed., Springer, New York, 2002. Search in Google Scholar

[6] K. Cooray, Analyzing lifetime data with long-tailed skewed distribution: The logistic-sinh family, Stat. Model. 5 (2005), no. 4, 343–358. 10.1191/1471082X05st099oaSearch in Google Scholar

[7] K. Cooray and M. M. A. Ananda, Analyzing survival data with highly negatively skewed distribution: The Gompertz-sinh family, J. Appl. Stat. 37 (2010), no. 1–2, 1–11. 10.1080/02664760802663072Search in Google Scholar

[8] K. Dedecius and P. Ettler, Overview of bounded support distributions and methods for Bayesian treatment of industrial data, Proceedings of the 10th International Conference on Informatics in Control, Automation and Robotics (ICINCO), Scitepress, Setúbal (2013), 380–387. Search in Google Scholar

[9] S. Dey, I. Ghosh and D. Kumar, Alpha-power transformed Lindley distribution: Properties and associated inference with application to earthquake data, Ann. Data. Sci. 6 (2019), 623–650. 10.1007/s40745-018-0163-2Search in Google Scholar

[10] S. Dey, M. Nassar and D. Kumar, Alpha power transformed inverse Lindley distribution: A distribution with an upside-down bathtub-shaped hazard function, J. Comput. Appl. Math. 348 (2019), 130–145. 10.1016/j.cam.2018.03.037Search in Google Scholar

[11] M. E. Ghitany, D. K. Al-Mutairi and S. Nadarajah, Zero-truncated Poisson–Lindley distribution and its application, Math. Comput. Simulation 79 (2008), no. 3, 279–287. 10.1016/j.matcom.2007.11.021Search in Google Scholar

[12] M. E. Ghitany, F. Alqallaf, D. K. Al-Mutairi and H. A. Husain, A two-parameter weighted Lindley distribution and its applications to survival data, Math. Comput. Simulation 81 (2011), no. 6, 1190–1201. 10.1016/j.matcom.2010.11.005Search in Google Scholar

[13] M. E. Ghitany, B. Atieh and S. Nadarajah, Lindley distribution and its application, Math. Comput. Simulation 78 (2008), no. 4, 493–506. 10.1016/j.matcom.2007.06.007Search in Google Scholar

[14] R. E. Glaser, Bathtub and related failure rate characterizations, J. Amer. Statist. Assoc. 75 (1980), no. 371, 667–672. 10.21236/ADA072626Search in Google Scholar

[15] I. S. Gradshteyn and I. M. Ryzhik, Table of Integrals, Series, and Products, 6th ed., Academic Press, San Diego, 2000. Search in Google Scholar

[16] R. Jiang, A new bathtub curve model with finite support, Reliab. Eng. Syst. Safety 119 (2013), 44–51. 10.1016/j.ress.2013.05.019Search in Google Scholar

[17] D. V. Lindley, Fiducial distributions and Bayes’ theorem, J. Roy. Statist. Soc. Ser. B 20 (1958), 102–107. 10.1111/j.2517-6161.1958.tb00278.xSearch in Google Scholar

[18] A. W. Marshall and I. Olkin, Life Distributions: Structure of Nonparametric, Semiparametric, and Parametric Families, Springer Ser. Statist., Springer, New York, 2007. Search in Google Scholar

[19] S. Maximov, V. H. Coria, F. Rivas-Davalos, R. Escarela-Perez and J. C. Olivares-Galvan, New analytical method for estimating mean life of electric power equipment based on complete and right-censored failure data, Electric Power Syst. Res. 154 (2017), 311–318. 10.1016/j.epsr.2017.08.042Search in Google Scholar

[20] S. Nadarajah, H. S. Bakouch and R. Tahmasbi, A generalized Lindley distribution, Sankhya B 73 (2011), no. 2, 331–359. 10.1007/s13571-011-0025-9Search in Google Scholar

[21] A. Rényi, On measures of entropy and information, Proceedings of the 4th Berkeley Symposium on Mathematical Statistics and Probability, University of California, Berkeley (1961), 547–561. Search in Google Scholar

[22] M. Sankaran, The discrete poisson-Lindley distribution, Biometrics 26 (1970), no. 1, 145–149. 10.2307/2529053Search in Google Scholar

[23] R. Shanker, S. Sharma and R. Shanker, A two-parameter lindley distribution for modeling waiting and survival times data, Appl. Math. 4 (2013), 363–368. 10.4236/am.2013.42056Search in Google Scholar

[24] V. K. Sharma, S. K. Singh, U. Singh and V. Agiwal, The inverse Lindley distribution: A stress-strength reliability model with application to head and neck cancer data, J. Ind. Production Eng. 32 (2015), no. 3, 162–173. 10.1080/21681015.2015.1025901Search in Google Scholar

[25] P. Sprent and N. C. Smeeton, Applied Nonparametric Statistical Methods, 4th ed., Chapman & Hall/CRC, Boca Raton 2007. Search in Google Scholar

[26] A. R. Thatcher, The longterm pattern of adult mortality and the highest attained age, J. Roy. Statist. Soc. Ser. A 162 (1999), 5–43. 10.1111/1467-985X.00119Search in Google Scholar

[27] H. Zakerzadeh and A. Dolati, Generalized Lindley distribution, J. Math. Ext. 3 (2009), no. 2, 13–25. Search in Google Scholar

Received: 2020-06-06
Revised: 2020-10-22
Accepted: 2020-10-22
Published Online: 2020-11-10
Published in Print: 2020-12-01

© 2020 Walter de Gruyter GmbH, Berlin/Boston

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