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The Lindley family of distributions: properties and applications

Year 2017, Volume: 46 Issue: 6, 1113 - 1137, 01.12.2017

Abstract

In this paper, we propose a new class of distributions called the Lindley generator with one extra parameter to generate many continuous distributions. The new distribution contains several distributions as submodels, such as Lindley-Exponential, Lindley-Weibull, and Lindley- Lomax. Some mathematical properties of the new generator, including ordinary moments, quantile and generating functions, limiting behaviors,
some entropy measures and order statistics, which hold for any baseline model, are presented. Then, we discuss the maximum likelihood
method to estimate model parameters. The importance of the new generator is illustrated by means of three real data sets. Applications
show that the new family of distributions can provide a better fit than several existing lifetime models.

References

  • A.N. Marshall and I. Olkin, A new method for adding a parameter to a family of distributions with applications to the exponential and Weibull families, Biometrika 84,641-552, (1997).
  • N. Eugene, C. Lee and F. Famoye, Beta-normal distribution and its applications, Commun Stat Theory 31,497-512,(2002).
  • G.M. Cordeiro and M.D. Castro, A new family of generalized distributions, J Statist Comput Simulation, 81, 883-898, (2011).
  • C. Alexander, G.M. Cordeiro, E.M.M Ortega and J.M. Sarabia, Generalized beta-generated distributions, Comput Stat Data An 56, 1880-1897, (2012).
  • A. Alzaatreh, C. Lee and F. Famoye, A new method for generating families of distributions, Metron 71, 63-79, (2013).
  • A. Alzaghal, F. Famoye ,C. Lee, Exponentiated T-X family of distributions with some applications, Int J Prob Stat 2, 31–49,(2013).
  • M. Bourguignon, R.B. Silva, G.M. Cordeiro, , The Weibull-G family of probability distributions, J Data Sci 12, 53-68,(2014).
  • G.M. Cordeiro, M. Alizadehand, E.M.M. Ortega,The exponentiated half-logistic family of distributions: properties and applications, J Prob Stat doi:10.1155/2014/864396 (2014).
  • G.M. Cordeiro, E.M.M. Ortega., B. Popovic, R.R. Pescim, The Lomax generator of distributions: Properties, minification process and regression model, Appl Math Comput 247, 465-486, (2014).
  • S. Nadarajah, G.M. Cordeiro, E.M.M. Ortega, The Zografos–Balakrishnan-G family of distributions: mathematical properties and applications, Commun Stat Theory 44, 186- 215,(2015).
  • D.V. Lindley, Fiducial distributions and Bayes’ theorem, J Roy Stat Soc B 20, 102- 107,(1958).
  • H.S. Bakouch, M.A. Bander, A.A. Al-Shaomrani, V.A.A. Marchi and F. Louzada, An extended Lindley distribution, J Korean Stat Soc 41, 75-85, (2012).
  • M.E. Ghitany, B. Atieh and S. Nadarajah, Lindley distribution and its application, Math Comput Simulat 78 493-506, (2008).
  • M.E. Ghitany, F. Alqallaf, D. K. Al-Mutairi and H.A. Husain, A two-parameter Lindley distribution and its applications to survival data, Math Comput Simulat 81, 1190–1201, (2011).
  • J. Mazucheli and J.A. Achcar, The Lindley distribution applied to competing risks lifetime data, Comput Meth Prog Bio 104, 188-92, (2011).
  • I.S. Gradshteyn and I.M. Ryzhik,Table of Integrals, Series and Products, Academic Press, New York, 2007.
  • G.S. Mudholkar and A.D. Hutson, The exponentiated Weibull family: some properties and a flood data application, Commun Stat Theory Meth 25, 3059-3083, (1996).
  • G.S. Mudholkar and D.K. Srivastava, , Exponentiated Weibull family for analyzing bathtub failure-rate data, IEEE Trans Rel 42, 299-302, (1993).
  • G.S. Mudholkar, D.K. Srivastava and M. Freimer, The exponentiated Weibull family; a reanalysis of the bus motor failure data, Technometrics 37, 436-445, (1995).
  • R.C. Gupta, P. L. Gupta, and R. D. Gupta, Modeling failure time data by Lehmann alternatives, Commun Stat Theory 27, 887-904, (1998).
  • R D. Gupta and D. Kundu, Generalized Exponential Distributions , Aust NZ J Stat 41, 173-188, (1999).
  • R.D. Gupta and D. Kundu, Exponentiated Exponential Family; An Alternative to Gamma and Weibull, Biometrical J 33, 117-130, (2001).
  • R.D. Gupta and D. Kundu, Generalized Exponential Distributions: Different Methods of Estimation, J Stat Comput Sim 69, 315-338, (2001).
  • S. Nadarajah and A.K. Gupta, A generalized gamma distribution with application to drought data, Math Comput Simulat 74, 1-7, (2007).
  • G.M. Cordeiro, S. Nadarajah and E.M.M. Ortega, The Kumaraswamy Gumbel distribution, Statist Meth Applic 21, 139-168, (2012).
  • M.A.R. Pascoa, E.M.M. Ortega, and G.M. Cordeiro, The Kumaraswamy generalized gamma distribution with application in survival analysis, Statist Methodol 8, 411–433, (2011).
  • P.F. Parana’ıba, E.M.M. Ortega, G.M. Cordeiro and M.A.R. Pascoa, The Kumaraswamy Burr XII distribution: theory and practice, J Stat Comput Sim 82, 1–27, (2012).
  • S. Nadarajah, G.M. Cordeiro and E.M.M. Ortega, General results for the Kumaraswamy-G distribution, J Stat Comput Sim, 951-972, (2012).
  • A.J. Lemonte, W. Barreto-Souza and G.M. Cordeiro, The exponentiated Kumaraswamy distribution and its log-transform, Braz J Probab Statist 27 31-53, (2013).
  • S. Nadarajah, G.M. Cordeiro, and E. M. Ortega, General results for the Kumaraswamy-G distribution, J Stat Comput Sim 82 951-979, (2012).
  • A. Renyi, On measures of entropy and information, In: Proceedings of the 4th Berkeley Symposium on Mathematical Statistics and Probability, 547-561. University of California Press, Berkeley, 1961.
  • C.E. Shannon, Prediction and entropy of printed English, Bell Syst Tech J 30, 50-64, (1951).
  • J.A. Doornik, Ox 5: An Object-Oriented Matrix Programming Language, Timberlake Consultants, London, 2007.
  • G. Ozel and S. Cakmakyapan, A new approach to the prediction of PM10 concentrations in Central Anatolia Region, Turkey, Atmos Pollut Res 6, 735-741, (2015).
  • A. Akdemir, The creation of pollution mapping and measurement of ambient concentration of sulfur dioxide and nitrogen dioxide with passive sampler, J Environ Health Sci Eng 12, (2014).
  • E.E. Ukpebor, S.I. Ahonkhal and H. Heydtman, NO2 measurement with passive sampler: assessment of the sensitivity of two types of palmes diffusion tubes for NO2, Intern J Environ Studies 61, 67-71, (2004).
  • T. Banerjee, S.B. Singh and R.K. Srivastava, Development and performance evaluation of statistical models correlating air pollutants and meteorological variables at Pantnagar, India Atmos Res 99 505-517, (2011).
Year 2017, Volume: 46 Issue: 6, 1113 - 1137, 01.12.2017

Abstract

References

  • A.N. Marshall and I. Olkin, A new method for adding a parameter to a family of distributions with applications to the exponential and Weibull families, Biometrika 84,641-552, (1997).
  • N. Eugene, C. Lee and F. Famoye, Beta-normal distribution and its applications, Commun Stat Theory 31,497-512,(2002).
  • G.M. Cordeiro and M.D. Castro, A new family of generalized distributions, J Statist Comput Simulation, 81, 883-898, (2011).
  • C. Alexander, G.M. Cordeiro, E.M.M Ortega and J.M. Sarabia, Generalized beta-generated distributions, Comput Stat Data An 56, 1880-1897, (2012).
  • A. Alzaatreh, C. Lee and F. Famoye, A new method for generating families of distributions, Metron 71, 63-79, (2013).
  • A. Alzaghal, F. Famoye ,C. Lee, Exponentiated T-X family of distributions with some applications, Int J Prob Stat 2, 31–49,(2013).
  • M. Bourguignon, R.B. Silva, G.M. Cordeiro, , The Weibull-G family of probability distributions, J Data Sci 12, 53-68,(2014).
  • G.M. Cordeiro, M. Alizadehand, E.M.M. Ortega,The exponentiated half-logistic family of distributions: properties and applications, J Prob Stat doi:10.1155/2014/864396 (2014).
  • G.M. Cordeiro, E.M.M. Ortega., B. Popovic, R.R. Pescim, The Lomax generator of distributions: Properties, minification process and regression model, Appl Math Comput 247, 465-486, (2014).
  • S. Nadarajah, G.M. Cordeiro, E.M.M. Ortega, The Zografos–Balakrishnan-G family of distributions: mathematical properties and applications, Commun Stat Theory 44, 186- 215,(2015).
  • D.V. Lindley, Fiducial distributions and Bayes’ theorem, J Roy Stat Soc B 20, 102- 107,(1958).
  • H.S. Bakouch, M.A. Bander, A.A. Al-Shaomrani, V.A.A. Marchi and F. Louzada, An extended Lindley distribution, J Korean Stat Soc 41, 75-85, (2012).
  • M.E. Ghitany, B. Atieh and S. Nadarajah, Lindley distribution and its application, Math Comput Simulat 78 493-506, (2008).
  • M.E. Ghitany, F. Alqallaf, D. K. Al-Mutairi and H.A. Husain, A two-parameter Lindley distribution and its applications to survival data, Math Comput Simulat 81, 1190–1201, (2011).
  • J. Mazucheli and J.A. Achcar, The Lindley distribution applied to competing risks lifetime data, Comput Meth Prog Bio 104, 188-92, (2011).
  • I.S. Gradshteyn and I.M. Ryzhik,Table of Integrals, Series and Products, Academic Press, New York, 2007.
  • G.S. Mudholkar and A.D. Hutson, The exponentiated Weibull family: some properties and a flood data application, Commun Stat Theory Meth 25, 3059-3083, (1996).
  • G.S. Mudholkar and D.K. Srivastava, , Exponentiated Weibull family for analyzing bathtub failure-rate data, IEEE Trans Rel 42, 299-302, (1993).
  • G.S. Mudholkar, D.K. Srivastava and M. Freimer, The exponentiated Weibull family; a reanalysis of the bus motor failure data, Technometrics 37, 436-445, (1995).
  • R.C. Gupta, P. L. Gupta, and R. D. Gupta, Modeling failure time data by Lehmann alternatives, Commun Stat Theory 27, 887-904, (1998).
  • R D. Gupta and D. Kundu, Generalized Exponential Distributions , Aust NZ J Stat 41, 173-188, (1999).
  • R.D. Gupta and D. Kundu, Exponentiated Exponential Family; An Alternative to Gamma and Weibull, Biometrical J 33, 117-130, (2001).
  • R.D. Gupta and D. Kundu, Generalized Exponential Distributions: Different Methods of Estimation, J Stat Comput Sim 69, 315-338, (2001).
  • S. Nadarajah and A.K. Gupta, A generalized gamma distribution with application to drought data, Math Comput Simulat 74, 1-7, (2007).
  • G.M. Cordeiro, S. Nadarajah and E.M.M. Ortega, The Kumaraswamy Gumbel distribution, Statist Meth Applic 21, 139-168, (2012).
  • M.A.R. Pascoa, E.M.M. Ortega, and G.M. Cordeiro, The Kumaraswamy generalized gamma distribution with application in survival analysis, Statist Methodol 8, 411–433, (2011).
  • P.F. Parana’ıba, E.M.M. Ortega, G.M. Cordeiro and M.A.R. Pascoa, The Kumaraswamy Burr XII distribution: theory and practice, J Stat Comput Sim 82, 1–27, (2012).
  • S. Nadarajah, G.M. Cordeiro and E.M.M. Ortega, General results for the Kumaraswamy-G distribution, J Stat Comput Sim, 951-972, (2012).
  • A.J. Lemonte, W. Barreto-Souza and G.M. Cordeiro, The exponentiated Kumaraswamy distribution and its log-transform, Braz J Probab Statist 27 31-53, (2013).
  • S. Nadarajah, G.M. Cordeiro, and E. M. Ortega, General results for the Kumaraswamy-G distribution, J Stat Comput Sim 82 951-979, (2012).
  • A. Renyi, On measures of entropy and information, In: Proceedings of the 4th Berkeley Symposium on Mathematical Statistics and Probability, 547-561. University of California Press, Berkeley, 1961.
  • C.E. Shannon, Prediction and entropy of printed English, Bell Syst Tech J 30, 50-64, (1951).
  • J.A. Doornik, Ox 5: An Object-Oriented Matrix Programming Language, Timberlake Consultants, London, 2007.
  • G. Ozel and S. Cakmakyapan, A new approach to the prediction of PM10 concentrations in Central Anatolia Region, Turkey, Atmos Pollut Res 6, 735-741, (2015).
  • A. Akdemir, The creation of pollution mapping and measurement of ambient concentration of sulfur dioxide and nitrogen dioxide with passive sampler, J Environ Health Sci Eng 12, (2014).
  • E.E. Ukpebor, S.I. Ahonkhal and H. Heydtman, NO2 measurement with passive sampler: assessment of the sensitivity of two types of palmes diffusion tubes for NO2, Intern J Environ Studies 61, 67-71, (2004).
  • T. Banerjee, S.B. Singh and R.K. Srivastava, Development and performance evaluation of statistical models correlating air pollutants and meteorological variables at Pantnagar, India Atmos Res 99 505-517, (2011).
There are 37 citations in total.

Details

Primary Language English
Subjects Mathematical Sciences
Journal Section Statistics
Authors

Selen Cakmakyapan This is me

Gamze Ozel

Publication Date December 1, 2017
Published in Issue Year 2017 Volume: 46 Issue: 6

Cite

APA Cakmakyapan, S., & Ozel, G. (2017). The Lindley family of distributions: properties and applications. Hacettepe Journal of Mathematics and Statistics, 46(6), 1113-1137.
AMA Cakmakyapan S, Ozel G. The Lindley family of distributions: properties and applications. Hacettepe Journal of Mathematics and Statistics. December 2017;46(6):1113-1137.
Chicago Cakmakyapan, Selen, and Gamze Ozel. “The Lindley Family of Distributions: Properties and Applications”. Hacettepe Journal of Mathematics and Statistics 46, no. 6 (December 2017): 1113-37.
EndNote Cakmakyapan S, Ozel G (December 1, 2017) The Lindley family of distributions: properties and applications. Hacettepe Journal of Mathematics and Statistics 46 6 1113–1137.
IEEE S. Cakmakyapan and G. Ozel, “The Lindley family of distributions: properties and applications”, Hacettepe Journal of Mathematics and Statistics, vol. 46, no. 6, pp. 1113–1137, 2017.
ISNAD Cakmakyapan, Selen - Ozel, Gamze. “The Lindley Family of Distributions: Properties and Applications”. Hacettepe Journal of Mathematics and Statistics 46/6 (December 2017), 1113-1137.
JAMA Cakmakyapan S, Ozel G. The Lindley family of distributions: properties and applications. Hacettepe Journal of Mathematics and Statistics. 2017;46:1113–1137.
MLA Cakmakyapan, Selen and Gamze Ozel. “The Lindley Family of Distributions: Properties and Applications”. Hacettepe Journal of Mathematics and Statistics, vol. 46, no. 6, 2017, pp. 1113-37.
Vancouver Cakmakyapan S, Ozel G. The Lindley family of distributions: properties and applications. Hacettepe Journal of Mathematics and Statistics. 2017;46(6):1113-37.