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Estimation of stress-strength probability in a multicomponent model based on geometric distribution

Year 2020, , 1515 - 1532, 06.08.2020
https://doi.org/10.15672/hujms.681608

Abstract

In this paper, the estimation of the stress-strength probability in a multicomponent model, in the case when all components follow the geometric distribution, is studied. This is the first time that multicomponent models with discrete probability distributions are considered. The MLE, UMVUE and Bayes point estimator, as well as asymptotic and bootstrap confidence intervals are presented. A simulation study is performed in order to compare the performance of various estimators. Finally, the methods are applied to real data examples from climatology and sport.

Supporting Institution

Ministarstvo prosvete, nauke i tehnološkog razvoja Republike Srbije (first and second author)

Project Number

174012

References

  • [1] K. E. Ahmad, M. E. Fakhry and Z. F. Jaheen, Bayes estimation of ${P}({Y}> {X})$ in the geometric case, Microelectronics Reliability 35 (5), 817–820, 1995.
  • [2] F. Akgül, Reliability estimation in multicomponent stress–strength model for Topp- Leone distribution, J. Stat. Comput. Simul. 89 (15), 2914–2929, 2019.
  • [3] A. Barbiero, Inference on reliability of stress-strength models for Poisson data, Journal of Quality and Reliability Engineering 2013, 2013.
  • [4] G. K. Bhattacharyya and R. A. Johnson, Estimation of reliability in a multicomponent stress-strength model, J. Amer. Statist. Assoc. 69 (348), 966–970, 1974.
  • [5] S. Dey, J. Mazucheli and M. Z. Anis, Estimation of reliability of multicomponent stress–strength for a Kumaraswamy distribution, Comm. Statist. Theory Methods 46 (4), 1560–1572, 2017.
  • [6] E. Furrer, R. Katz, M. Walter and R. Furrer, Statistical modeling of hot spells and heat waves, Climate Research 43 (3), 191–205, 2010.
  • [7] S. Gunasekera, Classical, Bayesian, and generalized inferences of the reliability of a multicomponent system with censored data, J. Stat. Comput. Simul. 88 (18), 3455– 3501, 2018.
  • [8] R. V. Hogg, J. McKean and A. T. Craig, Introduction to Mathematical Statistics, 7th Edition, Pearson Prentice Hall, 2013.
  • [9] V. V. Ivshin and Ya.. P. Lumelskii, Statistical estimation problems in stress-strength models, Perm University Press, Perm, 1995.
  • [10] M. Jovanović, Estimation of {P}$\{{X}<{Y}\}$ for geometric-exponential model based on complete and censored sample, Comm. Statist. Simulation Comput. 46 (4), 3050– 3066, 2017.
  • [11] T. Kayal, Y. M. Tripathi, S. Dey and S. J. Wu, On estimating the reliability in a multicomponent stress-strength model based on Chen distribution, Comm. Statist. Theory Methods 49 (10), 2429–2447, 2020.
  • [12] D. Kendall and J. Dracup, On the generation of drought events using an alternating renewal-reward model, Stochastic Hydrology and Hydraulics 6 (1), 55–68, 1992.
  • [13] F. Kızılaslan, Classical and Bayesian estimation of reliability in a multicomponent stress–strength model based on a general class of inverse exponentiated distributions, Statist. Papers 59 (3), 1161–1192, 2018.
  • [14] F. Kizilaslan and M. Nadar, Classical and Bayesian estimation of reliability in multicomponent stress-strength model based on Weibull distribution, Revista Colombiana de Estadística 38 (2), 467–484, 2015.
  • [15] F. Kızılaslan and M. Nadar, Estimation of reliability in a multicomponent stress– strength model based on a bivariate Kumaraswamy distribution, Statist. Papers 59 (1), 307–340, 2018.
  • [16] A. Kohansal, On estimation of reliability in a multicomponent stress-strength model for a Kumaraswamy distribution based on progressively censored sample, Statist. Papers 60 (6), 2185–2224, 2019.
  • [17] S. Kotz, Y. Lumelskii and M. Pensky, The stress–strength model and its generalizations: theory and applications, World Scientific, 2003.
  • [18] S. S. Maiti, Estimation of {P}$({X}\leq {Y})$ in the geometric case, J. Indian Statist. Assoc. 33 (2), 87–91, 1995.
  • [19] M. Obradović, M. Jovanović and B. Milosević, Optimal unbiased estimates of {P}$\{${X}$<${Y}$\}$ for some families of distributions, Metodološki zvezki 11 (1), 21–29, 2014.
  • [20] M. Obradović, M. Jovanović, B. Milošević and V. Jevremović, Estimation of {P}$\{$X$\leq$Y$\}$ for geometric-Poisson model, Hacet. J. Math. Stat. 44 (4), 949–964, 2015.
  • [21] A. Pak, A. K. Gupta and N. B. Khoolenjani, On reliability in a multicomponent stress strength model with power Lindley distribution, Revista Colombiana de Estadística 41 (2), 251–267, 2018.
  • [22] G. S. Rao, Estimation of reliability in multicomponent stress-strength based on generalized exponential distribution, Revista Colombiana de Estadística 35 (1), 67–76, 2012.
  • [23] G. S. Rao, M. Aslam and O. H. Arif, Estimation of reliability in multicomponent stress–strength based on two parameter exponentiated Weibull distribution, Comm. Statist. Theory Methods 46 (15), 7495–7502, 2017.
  • [24] G. S. Rao, M. Aslam and D. Kundu, Burr-XII distribution parametric estimation and estimation of reliability of multicomponent stress-strength, Comm. Statist. Theory Methods 44 (23), 4953–4961, 2015.
  • [25] Y. S. Sathe and U. J. Dixit, Estimation of {P}$[{X}\leq{Y}]$ in the negative binomial distribution, J. Statist. Plann. Inference 93 (1), 83–92, 2001.
Year 2020, , 1515 - 1532, 06.08.2020
https://doi.org/10.15672/hujms.681608

Abstract

Project Number

174012

References

  • [1] K. E. Ahmad, M. E. Fakhry and Z. F. Jaheen, Bayes estimation of ${P}({Y}> {X})$ in the geometric case, Microelectronics Reliability 35 (5), 817–820, 1995.
  • [2] F. Akgül, Reliability estimation in multicomponent stress–strength model for Topp- Leone distribution, J. Stat. Comput. Simul. 89 (15), 2914–2929, 2019.
  • [3] A. Barbiero, Inference on reliability of stress-strength models for Poisson data, Journal of Quality and Reliability Engineering 2013, 2013.
  • [4] G. K. Bhattacharyya and R. A. Johnson, Estimation of reliability in a multicomponent stress-strength model, J. Amer. Statist. Assoc. 69 (348), 966–970, 1974.
  • [5] S. Dey, J. Mazucheli and M. Z. Anis, Estimation of reliability of multicomponent stress–strength for a Kumaraswamy distribution, Comm. Statist. Theory Methods 46 (4), 1560–1572, 2017.
  • [6] E. Furrer, R. Katz, M. Walter and R. Furrer, Statistical modeling of hot spells and heat waves, Climate Research 43 (3), 191–205, 2010.
  • [7] S. Gunasekera, Classical, Bayesian, and generalized inferences of the reliability of a multicomponent system with censored data, J. Stat. Comput. Simul. 88 (18), 3455– 3501, 2018.
  • [8] R. V. Hogg, J. McKean and A. T. Craig, Introduction to Mathematical Statistics, 7th Edition, Pearson Prentice Hall, 2013.
  • [9] V. V. Ivshin and Ya.. P. Lumelskii, Statistical estimation problems in stress-strength models, Perm University Press, Perm, 1995.
  • [10] M. Jovanović, Estimation of {P}$\{{X}<{Y}\}$ for geometric-exponential model based on complete and censored sample, Comm. Statist. Simulation Comput. 46 (4), 3050– 3066, 2017.
  • [11] T. Kayal, Y. M. Tripathi, S. Dey and S. J. Wu, On estimating the reliability in a multicomponent stress-strength model based on Chen distribution, Comm. Statist. Theory Methods 49 (10), 2429–2447, 2020.
  • [12] D. Kendall and J. Dracup, On the generation of drought events using an alternating renewal-reward model, Stochastic Hydrology and Hydraulics 6 (1), 55–68, 1992.
  • [13] F. Kızılaslan, Classical and Bayesian estimation of reliability in a multicomponent stress–strength model based on a general class of inverse exponentiated distributions, Statist. Papers 59 (3), 1161–1192, 2018.
  • [14] F. Kizilaslan and M. Nadar, Classical and Bayesian estimation of reliability in multicomponent stress-strength model based on Weibull distribution, Revista Colombiana de Estadística 38 (2), 467–484, 2015.
  • [15] F. Kızılaslan and M. Nadar, Estimation of reliability in a multicomponent stress– strength model based on a bivariate Kumaraswamy distribution, Statist. Papers 59 (1), 307–340, 2018.
  • [16] A. Kohansal, On estimation of reliability in a multicomponent stress-strength model for a Kumaraswamy distribution based on progressively censored sample, Statist. Papers 60 (6), 2185–2224, 2019.
  • [17] S. Kotz, Y. Lumelskii and M. Pensky, The stress–strength model and its generalizations: theory and applications, World Scientific, 2003.
  • [18] S. S. Maiti, Estimation of {P}$({X}\leq {Y})$ in the geometric case, J. Indian Statist. Assoc. 33 (2), 87–91, 1995.
  • [19] M. Obradović, M. Jovanović and B. Milosević, Optimal unbiased estimates of {P}$\{${X}$<${Y}$\}$ for some families of distributions, Metodološki zvezki 11 (1), 21–29, 2014.
  • [20] M. Obradović, M. Jovanović, B. Milošević and V. Jevremović, Estimation of {P}$\{$X$\leq$Y$\}$ for geometric-Poisson model, Hacet. J. Math. Stat. 44 (4), 949–964, 2015.
  • [21] A. Pak, A. K. Gupta and N. B. Khoolenjani, On reliability in a multicomponent stress strength model with power Lindley distribution, Revista Colombiana de Estadística 41 (2), 251–267, 2018.
  • [22] G. S. Rao, Estimation of reliability in multicomponent stress-strength based on generalized exponential distribution, Revista Colombiana de Estadística 35 (1), 67–76, 2012.
  • [23] G. S. Rao, M. Aslam and O. H. Arif, Estimation of reliability in multicomponent stress–strength based on two parameter exponentiated Weibull distribution, Comm. Statist. Theory Methods 46 (15), 7495–7502, 2017.
  • [24] G. S. Rao, M. Aslam and D. Kundu, Burr-XII distribution parametric estimation and estimation of reliability of multicomponent stress-strength, Comm. Statist. Theory Methods 44 (23), 4953–4961, 2015.
  • [25] Y. S. Sathe and U. J. Dixit, Estimation of {P}$[{X}\leq{Y}]$ in the negative binomial distribution, J. Statist. Plann. Inference 93 (1), 83–92, 2001.
There are 25 citations in total.

Details

Primary Language English
Subjects Statistics
Journal Section Statistics
Authors

Milan Jovanovıć 0000-0001-5512-0956

Bojana Milošević This is me 0000-0001-8243-9794

Marko Obradović This is me 0000-0002-6826-3232

Project Number 174012
Publication Date August 6, 2020
Published in Issue Year 2020

Cite

APA Jovanovıć, M., Milošević, B., & Obradović, M. (2020). Estimation of stress-strength probability in a multicomponent model based on geometric distribution. Hacettepe Journal of Mathematics and Statistics, 49(4), 1515-1532. https://doi.org/10.15672/hujms.681608
AMA Jovanovıć M, Milošević B, Obradović M. Estimation of stress-strength probability in a multicomponent model based on geometric distribution. Hacettepe Journal of Mathematics and Statistics. August 2020;49(4):1515-1532. doi:10.15672/hujms.681608
Chicago Jovanovıć, Milan, Bojana Milošević, and Marko Obradović. “Estimation of Stress-Strength Probability in a Multicomponent Model Based on Geometric Distribution”. Hacettepe Journal of Mathematics and Statistics 49, no. 4 (August 2020): 1515-32. https://doi.org/10.15672/hujms.681608.
EndNote Jovanovıć M, Milošević B, Obradović M (August 1, 2020) Estimation of stress-strength probability in a multicomponent model based on geometric distribution. Hacettepe Journal of Mathematics and Statistics 49 4 1515–1532.
IEEE M. Jovanovıć, B. Milošević, and M. Obradović, “Estimation of stress-strength probability in a multicomponent model based on geometric distribution”, Hacettepe Journal of Mathematics and Statistics, vol. 49, no. 4, pp. 1515–1532, 2020, doi: 10.15672/hujms.681608.
ISNAD Jovanovıć, Milan et al. “Estimation of Stress-Strength Probability in a Multicomponent Model Based on Geometric Distribution”. Hacettepe Journal of Mathematics and Statistics 49/4 (August 2020), 1515-1532. https://doi.org/10.15672/hujms.681608.
JAMA Jovanovıć M, Milošević B, Obradović M. Estimation of stress-strength probability in a multicomponent model based on geometric distribution. Hacettepe Journal of Mathematics and Statistics. 2020;49:1515–1532.
MLA Jovanovıć, Milan et al. “Estimation of Stress-Strength Probability in a Multicomponent Model Based on Geometric Distribution”. Hacettepe Journal of Mathematics and Statistics, vol. 49, no. 4, 2020, pp. 1515-32, doi:10.15672/hujms.681608.
Vancouver Jovanovıć M, Milošević B, Obradović M. Estimation of stress-strength probability in a multicomponent model based on geometric distribution. Hacettepe Journal of Mathematics and Statistics. 2020;49(4):1515-32.