Estimation of stress-strength probability in a multicomponent model based on geometric distribution
Year 2020,
, 1515 - 1532, 06.08.2020
Milan Jovanovıć
,
Bojana Milošević
Marko Obradović
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)
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
Milan Jovanovıć
,
Bojana Milošević
Marko Obradović
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.