On the estimation of the stress-strength parameter for the inverse Lindley distribution based on lower record values
Year 2025,
Volume: 54 Issue: 1, 291 - 318, 28.02.2025
Bahareh Etemad Golestani
,
Ehsan Ormoz
,
S.m.t.k. Mirmostafaee
Abstract
In this article, we consider the estimation of the stress-strength reliability parameter for the inverse Lindley distribution based on lower record values. The maximum likelihood estimator and its asymptotic distribution are obtained. An approximate classical confidence interval, as well as two bootstrap-type confidence intervals for the reliability parameter are derived. The Bayesian inference for the parameter has been considered using Tierney and Kadane’s approximation method, as well as two Monte Carlo methods, namely the Metropolis-Hastings and importance sampling techniques under both symmetric and asymmetric loss functions. Besides, the Chen and Shao shortest width credible intervals are constructed for the stress-strength parameter. A simulation study and a real data example are conducted to explore and compare the performances of the presented results.
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two-parameter generalized exponential records, Comm. Statist. Simulation Comput.
46 (1), 379-394, 2017.
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exponential distributions, Comm. Statist. Theory Methods 37 (5), 692-698, 2008.
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values from the generalized exponential distribution, Comput. Statist. Data Anal. 52
(7), 3468-3473, 2008.
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on records, Appl. Math. Model. 38 (5-6), 1698-1709, 2014.
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exponential distribution based on records, J. Stat. Comput. Simul. 84 (12), 2670-2679,
2014.
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for Type-I censored data, Comput. Statist. 32 (1), 367-385, 2017.
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product of spacings function for hybrid censored data, Methodol. Comput. Appl.
Probab. 21 (4), 1377-1394, 2019.
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Weibull distribution, Microelectron. Reliab. 34 (5), 789-802, 1994.
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left-truncated exponential samples, Comm. Statist. Theory Methods 25 (3), 585-600,
1996.
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win.tue.nl/AppStat2013/files/lectures23.pdf.
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fuzzy data using inverse Lindley distribution, Austrian J. Stat. 52 (2), 86-103, 2023.
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intervals, J. Comput. Graph. Statist. 8 (1), 69-92, 1999.
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XII distributions with record samples, Comm. Statist. Simulation Comput. 47 (3),
822-838, 2018.
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Technometrics 12 (1), 49-54, 1970.
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reliability for generalized Gompertz distribution under progressive type-II censoring,
Hacet. J. Math. Stat. 52 (5), 1379-1395, 2023.
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in Reliability Theory: Methodology, Practice, and Inference, Eds. N. Limnios
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with decreasing and upside-down bathtub-shaped hazard rate function, Statistica
79 (4), 399-426, 2019.
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process capability indices for inverse Lindley distribution, Life Cycle Reliab.
Saf. Eng. 7 (2), 89-96, 2018.
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Regional Conference Series in Applied Mathematics 38, Philadelphia: Society for
Industrial and Applied Mathematics (SIAM), 1982.
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for the inverse Lindley distribution based on lower record values, REVSTAT, 2024,
https://revstat.ine.pt/index.php/REVSTAT/article/view/559.
- [28] M.K. Hassan, M.I. Alohali and F.A. Alojail, A new application of $R= P [Y< X]$ for
the inverse Lindley distribution using ranked set sampling, J. Stat. Manag. Syst. 24
(8), 1713-1731, 2021.
- [29] W.K. Hastings, Monte Carlo sampling methods using Markov chains and their applications,
Biometrika 57 (1), 97-109, 1970.
- [30] S. Joo and J. Mi, Some properties of hazard rate functions of systems with two components,
J. Statist. Plann. Inference 140 (2), 444-453, 2010.
- [31] A. Joukar, M. Ramezani and S.M.T.K. MirMostafaee, Estimation of $P (X> Y)$ for
the power Lindley distribution based on progressively type II right censored samples,
J. Stat. Comput. Simul. 90 (2), 355-389, 2020.
- [32] R.M. Juvairiyya and P. Anilkumar, Estimation of stress-strength reliability for the
Pareto distribution based on upper record values, Statistica 78 (4), 397-409, 2018.
- [33] A.C. Kimber, Exploratory data analysis for possibly censored data from skewed distributions,
J. Roy. Statist. Soc. Ser. C 39 (1), 21-30, 1990.
- [34] F. Kızılaslan and M. Nadar, Statistical inference of $ P (X< Y) $ for the Burr Type XII
distribution based on records, Hacet. J. Math. Stat. 46 (4), 713-742, 2017.
- [35] A.O. Langlands, S.J. Pocock, G.R. Kerr and S.M. Gore, Long-term survival of patients
with breast cancer: a study of the curability of the disease, Br. Med. J. 2 (6200), 1247-
1251, 1979.
- [36] J.F. Lawless, Statistical Models and Methods for Lifetime Data, 2nd Edition, Hoboken:
John Wiley & Sons, 2003.
- [37] I.S. Mabrouk, Statistical inference for the parameter of the inverse Lindley distribution
based on imprecise data with simulation study, Int. J. Contemp. Math. Sci. 14
(4), 151-161, 2019.
- [38] W.W. Maennig, Bemarken zur Beurteilung des dauerschwring Festigkeitsverhaltens
von Stahl und einige Untersuchungen zer Bestimmig des Dauerfestigkeitbereichs, Materialpruf
12, 124-131, 1967.
- [39] M.A.W. Mahmoud, R.M. El-Sagheer, A.A. Soliman and A.H. Abd Ellah, Bayesian
estimation of $P [Y< X]$ based on record values from the Lomax distribution and
MCMC technique, J. Mod. Appl. Stat. Methods 15 (1), 488-510, 2016.
- [40] J. Mazucheli, L.B. Fernandes and R.P. de Oliveira, LindleyR: The Lindley distribution
and its modifications, R package version 1.0.0, https://CRAN.R-project.org/
package=LindleyR, 2016.
- [41] O. Mersmann, H. Trautmann, D. Steuer and B. Bornkamp, truncnorm: Truncated
normal distribution. R package version 1.0-8, https://CRAN.R-project.org/
package=truncnorm, 2018.
- [42] N. Metropolis, A.W. Rosenbluth, M.N. Rosenbluth, A.H. Teller and E. Teller, Equations
of state calculations by fast computing machine, J. Chem. Phys. 21 (6), 1087-
1092, 1953.
- [43] M. Nadar and F. Kızılaslan, Classical and Bayesian estimation of $P (X< Y)$ using
upper record values from Kumaraswamy’s distribution, Statist. Papers 55 (3), 751-783,
2014.
- [44] Z. Pakdaman and R. Alizadeh Noughabi, On the study of the stress-strength reliability
in Weibull-F models, Hacet. J. Math. Stat. 53 (1), 269-288, 2024.
- [45] M. Plummer, N. Best, K. Cowles and K. Vines, CODA: Convergence diagnosis and
output analysis for MCMC, R News 6 (1), 7-11, 2006.
- [46] M. Plummer, N. Best, K. Cowles, K. Vines, D. Sarkar, D. Bates, R. Almond and A.
Magnusson, coda: Output analysis and diagnostics for MCMC. R package version
0.19-2, https://CRAN.R-project.org/package=coda, 2018.
- [47] R Core Team, A Language and Envirenment for Statistical Computing. R Foundation
for Statistical Computing, Vienna, Austria, 2020.
- [48] M. Ramezani, A. Joukar and S.M.T.K. MirMostafaee, Estimation of the stressstrength
parameter for a decreasing failure rate model based on ranked set samples. J.
Test. Eval. 52 (6), https://doi.org/10.1520/JTE20240072, 2024.
- [49] P.L. Ramos, F. Louzada, T.K. Shimizu and A.O. Luiz, The inverse weighted Lindley
distribution: Properties, estimation and an application on a failure time data, Comm.
Statist. Theory Methods 48 (10), 2372-2389, 2019.
- [50] C.P. Robert and G. Casella, Monte Carlo Statistical Methods, 2nd Edition, New York:
Springer, 2004.
- [51] S. Sen, A.Z. Afify, H. Al-Mofleh and M. Ahsanullah, The quasi xgamma-geometric
distribution with application in medicine, Filomat 33 (16), 5291-5330, 2019.
- [52] J. Shao, Mathematical Statistics, 2nd Edition, New York: Springer, 2003.
- [53] 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. Prod. Eng. 32 (3), 162-173, 2015.
- [54] W. Stute, W.G. Manteiga and M.P. Quindimil, Bootstrap based goodness-of-fit-tests,
Metrika 40 (1), 243-56, 1993.
- [55] C. Tanis, B. Saraçoglu, A. Asgharzadeh and M. Abdi, Estimation of $Pr (X< Y)$ for
exponential power records, Hacet. J. Math. Stat. 52 (2), 499-511, 2023.
- [56] B. Tarvirdizade and M. Ahmadpour, Estimation of the stress-strength reliability for
the two-parameter bathtub-shaped lifetime distribution based on upper record values,
Stat. Methodol. 31, 58-72, 2016.
- [57] B. Tarvirdizade and H. Kazemzadeh Gharehchobogh, Inference on $Pr (X> Y)$ based
on record values from the Burr Type X distribution, Hacet. J. Math. Stat. 45 (1),
267-278, 2016.
- [58] L. Tierney and J.B. Kadane, Accurate approximations for posterior moments and
marginal densities, J. Amer. Statist. Assoc. 81 (393), 82-86, 1986.
- [59] A. Tripathi, U. Singh and S.K. Singh, Estimation of $P (X< Y)$ for Gompertz distribution
based on upper records, Int. J. Model. Simul. 42 (3), 388-399, 2022.
- [60] H.R. Varian, A Bayesian approach to real estate assessment, in: Studies in Bayesian
Econometrics and Statistics in Honor of Leonard J. Savage, Eds. S.E. Fienberg and
A. Zellner, North-Holland Publishing Company, Amsterdam, 195-208, 1975.
- [61] L.A. Wasserman, All of Statistics: A Concise Course in Statistical Inference, New
York: Springer, 2004.
- [62] A.C.M. Wong, and Y.Y. Wu, A note on interval estimation of $P (X< Y)$ using lower
record data from the generalized exponential distribution, Comput. Statist. Data Anal.
53 (10), 3650-3658, 2009.
- [63] A. Zellner, Bayesian estimation and prediction using asymmetric loss functions, J.
Amer. Statist. Assoc. 81 (394), 446-451, 1986.
Year 2025,
Volume: 54 Issue: 1, 291 - 318, 28.02.2025
Bahareh Etemad Golestani
,
Ehsan Ormoz
,
S.m.t.k. Mirmostafaee
References
- [1] G.A. Abd-Elmougod and H.H. Abu-Zinadah, Estimation of $P (Y<X)$ for twoparameter
bathtub shape distribution using records: Bayesian and non-Bayesian approaches,
J. Comput. Theor. Nanosci. 14 (2), 1127-1135, 2017.
- [2] J. Albert, Bayesian Computation with R, 2nd Edition, Dordrecht: Springer, 2009.
- [3] R. Alotaibi, M. Nassar and A. Elshahhat, Statistical analysis of inverse Lindley data
using adaptive Type-II progressively hybrid censoring with applications, Axioms 12
(5), 427, 2023.
- [4] B.C. Arnold, N. Balakrishnan and H.N. Nagaraja, Records, New York: John Wiley
& Sons, 1998.
- [5] A. Asgharzadeh, M. Alizadeh and M.Z. Raqab, Inverse Lindley distribution: different
methods for estimating their PDF and CDF, J. Stat. Comput. Simul. 94 (3), 604-623,
2024.
- [6] A. Asgharzadeh, R. Valiollahi and M.Z. Raqab, Estimation of $Pr (Y<X)$ for the
two-parameter generalized exponential records, Comm. Statist. Simulation Comput.
46 (1), 379-394, 2017.
- [7] A. Baklizi, Estimation of $Pr (X<Y)$ using record values in the one and two parameter
exponential distributions, Comm. Statist. Theory Methods 37 (5), 692-698, 2008.
- [8] A. Baklizi, Likelihood and Bayesian estimation of $Pr (X<Y)$ using lower record
values from the generalized exponential distribution, Comput. Statist. Data Anal. 52
(7), 3468-3473, 2008.
- [9] A. Baklizi, Bayesian inference for $Pr (Y<X)$ in the exponential distribution based
on records, Appl. Math. Model. 38 (5-6), 1698-1709, 2014.
- [10] A. Baklizi, Interval estimation of the stress-strength reliability in the two-parameter
exponential distribution based on records, J. Stat. Comput. Simul. 84 (12), 2670-2679,
2014.
- [11] S. Basu, S.K. Singh and U. Singh, Parameter estimation of inverse Lindley distribution
for Type-I censored data, Comput. Statist. 32 (1), 367-385, 2017.
- [12] S. Basu, S.K. Singh and U. Singh, Estimation of inverse Lindley distribution using
product of spacings function for hybrid censored data, Methodol. Comput. Appl.
Probab. 21 (4), 1377-1394, 2019.
- [13] S. Bennett, Log-logistic regression models for survival data, J. Roy. Statist. Soc. Ser.
C 32 (2), 165-171, 1983.
- [14] R. Calabria and G. Pulcini, An engineering approach to Bayes estimation for the
Weibull distribution, Microelectron. Reliab. 34 (5), 789-802, 1994.
- [15] R. Calabria and G. Pulcini, Point estimation under asymmetric loss functions for
left-truncated exponential samples, Comm. Statist. Theory Methods 25 (3), 585-600,
1996.
- [16] R. Castro, Lectures 2 and 3 - Goodness-of-fit (GoF) Tests, 2013, https://rmcastro.
win.tue.nl/AppStat2013/files/lectures23.pdf.
- [17] A. Chaturvedi, S.K. Singh and U. Singh, Maximum product spacings estimator for
fuzzy data using inverse Lindley distribution, Austrian J. Stat. 52 (2), 86-103, 2023.
- [18] M.H. Chen and Q.M. Shao, Monte Carlo estimation of Bayesian credible and HPD
intervals, J. Comput. Graph. Statist. 8 (1), 69-92, 1999.
- [19] J.Y. Chiang, N. Jiang, T.R. Tsai and Y.L. Lio, Inference of $\delta= P (X< Y)$ for Burr
XII distributions with record samples, Comm. Statist. Simulation Comput. 47 (3),
822-838, 2018.
- [20] J.D. Church and B. Harris, The estimation of reliability from stress-strength relationships,
Technometrics 12 (1), 49-54, 1970.
- [21] F. Çiftci, B. Saraçoglu, N. Akdam and Y. Akdogan, Estimation of stress-strength
reliability for generalized Gompertz distribution under progressive type-II censoring,
Hacet. J. Math. Stat. 52 (5), 1379-1395, 2023.
- [22] M.J. Crowder, Tests for a family of survival models based on extremes, in: Recent Advances
in Reliability Theory: Methodology, Practice, and Inference, Eds. N. Limnios
and M. Nikulin, Birkhäuser, Boston, 307-321, 2000.
- [23] A.C. Davison and D.V. Hinkley, Bootstrap Methods and Their Application, Cambridge:
Cambridge University Press, 1997.
- [24] S. Dey, M. Nassar, D. Kumar, A. Alzaatreh and M.H. Tahir, A new lifetime distribution
with decreasing and upside-down bathtub-shaped hazard rate function, Statistica
79 (4), 399-426, 2019.
- [25] S. Dey and M. Saha, Bootstrap confidence intervals of the difference between two generalized
process capability indices for inverse Lindley distribution, Life Cycle Reliab.
Saf. Eng. 7 (2), 89-96, 2018.
- [26] B. Efron, The Jackknife, the Bootstrap and Other Resampling Plans, CBMS-NSF
Regional Conference Series in Applied Mathematics 38, Philadelphia: Society for
Industrial and Applied Mathematics (SIAM), 1982.
- [27] B. Etemad Golestani, E. Ormoz and S.M.T.K. MirMostafaee, Statistical inference
for the inverse Lindley distribution based on lower record values, REVSTAT, 2024,
https://revstat.ine.pt/index.php/REVSTAT/article/view/559.
- [28] M.K. Hassan, M.I. Alohali and F.A. Alojail, A new application of $R= P [Y< X]$ for
the inverse Lindley distribution using ranked set sampling, J. Stat. Manag. Syst. 24
(8), 1713-1731, 2021.
- [29] W.K. Hastings, Monte Carlo sampling methods using Markov chains and their applications,
Biometrika 57 (1), 97-109, 1970.
- [30] S. Joo and J. Mi, Some properties of hazard rate functions of systems with two components,
J. Statist. Plann. Inference 140 (2), 444-453, 2010.
- [31] A. Joukar, M. Ramezani and S.M.T.K. MirMostafaee, Estimation of $P (X> Y)$ for
the power Lindley distribution based on progressively type II right censored samples,
J. Stat. Comput. Simul. 90 (2), 355-389, 2020.
- [32] R.M. Juvairiyya and P. Anilkumar, Estimation of stress-strength reliability for the
Pareto distribution based on upper record values, Statistica 78 (4), 397-409, 2018.
- [33] A.C. Kimber, Exploratory data analysis for possibly censored data from skewed distributions,
J. Roy. Statist. Soc. Ser. C 39 (1), 21-30, 1990.
- [34] F. Kızılaslan and M. Nadar, Statistical inference of $ P (X< Y) $ for the Burr Type XII
distribution based on records, Hacet. J. Math. Stat. 46 (4), 713-742, 2017.
- [35] A.O. Langlands, S.J. Pocock, G.R. Kerr and S.M. Gore, Long-term survival of patients
with breast cancer: a study of the curability of the disease, Br. Med. J. 2 (6200), 1247-
1251, 1979.
- [36] J.F. Lawless, Statistical Models and Methods for Lifetime Data, 2nd Edition, Hoboken:
John Wiley & Sons, 2003.
- [37] I.S. Mabrouk, Statistical inference for the parameter of the inverse Lindley distribution
based on imprecise data with simulation study, Int. J. Contemp. Math. Sci. 14
(4), 151-161, 2019.
- [38] W.W. Maennig, Bemarken zur Beurteilung des dauerschwring Festigkeitsverhaltens
von Stahl und einige Untersuchungen zer Bestimmig des Dauerfestigkeitbereichs, Materialpruf
12, 124-131, 1967.
- [39] M.A.W. Mahmoud, R.M. El-Sagheer, A.A. Soliman and A.H. Abd Ellah, Bayesian
estimation of $P [Y< X]$ based on record values from the Lomax distribution and
MCMC technique, J. Mod. Appl. Stat. Methods 15 (1), 488-510, 2016.
- [40] J. Mazucheli, L.B. Fernandes and R.P. de Oliveira, LindleyR: The Lindley distribution
and its modifications, R package version 1.0.0, https://CRAN.R-project.org/
package=LindleyR, 2016.
- [41] O. Mersmann, H. Trautmann, D. Steuer and B. Bornkamp, truncnorm: Truncated
normal distribution. R package version 1.0-8, https://CRAN.R-project.org/
package=truncnorm, 2018.
- [42] N. Metropolis, A.W. Rosenbluth, M.N. Rosenbluth, A.H. Teller and E. Teller, Equations
of state calculations by fast computing machine, J. Chem. Phys. 21 (6), 1087-
1092, 1953.
- [43] M. Nadar and F. Kızılaslan, Classical and Bayesian estimation of $P (X< Y)$ using
upper record values from Kumaraswamy’s distribution, Statist. Papers 55 (3), 751-783,
2014.
- [44] Z. Pakdaman and R. Alizadeh Noughabi, On the study of the stress-strength reliability
in Weibull-F models, Hacet. J. Math. Stat. 53 (1), 269-288, 2024.
- [45] M. Plummer, N. Best, K. Cowles and K. Vines, CODA: Convergence diagnosis and
output analysis for MCMC, R News 6 (1), 7-11, 2006.
- [46] M. Plummer, N. Best, K. Cowles, K. Vines, D. Sarkar, D. Bates, R. Almond and A.
Magnusson, coda: Output analysis and diagnostics for MCMC. R package version
0.19-2, https://CRAN.R-project.org/package=coda, 2018.
- [47] R Core Team, A Language and Envirenment for Statistical Computing. R Foundation
for Statistical Computing, Vienna, Austria, 2020.
- [48] M. Ramezani, A. Joukar and S.M.T.K. MirMostafaee, Estimation of the stressstrength
parameter for a decreasing failure rate model based on ranked set samples. J.
Test. Eval. 52 (6), https://doi.org/10.1520/JTE20240072, 2024.
- [49] P.L. Ramos, F. Louzada, T.K. Shimizu and A.O. Luiz, The inverse weighted Lindley
distribution: Properties, estimation and an application on a failure time data, Comm.
Statist. Theory Methods 48 (10), 2372-2389, 2019.
- [50] C.P. Robert and G. Casella, Monte Carlo Statistical Methods, 2nd Edition, New York:
Springer, 2004.
- [51] S. Sen, A.Z. Afify, H. Al-Mofleh and M. Ahsanullah, The quasi xgamma-geometric
distribution with application in medicine, Filomat 33 (16), 5291-5330, 2019.
- [52] J. Shao, Mathematical Statistics, 2nd Edition, New York: Springer, 2003.
- [53] 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. Prod. Eng. 32 (3), 162-173, 2015.
- [54] W. Stute, W.G. Manteiga and M.P. Quindimil, Bootstrap based goodness-of-fit-tests,
Metrika 40 (1), 243-56, 1993.
- [55] C. Tanis, B. Saraçoglu, A. Asgharzadeh and M. Abdi, Estimation of $Pr (X< Y)$ for
exponential power records, Hacet. J. Math. Stat. 52 (2), 499-511, 2023.
- [56] B. Tarvirdizade and M. Ahmadpour, Estimation of the stress-strength reliability for
the two-parameter bathtub-shaped lifetime distribution based on upper record values,
Stat. Methodol. 31, 58-72, 2016.
- [57] B. Tarvirdizade and H. Kazemzadeh Gharehchobogh, Inference on $Pr (X> Y)$ based
on record values from the Burr Type X distribution, Hacet. J. Math. Stat. 45 (1),
267-278, 2016.
- [58] L. Tierney and J.B. Kadane, Accurate approximations for posterior moments and
marginal densities, J. Amer. Statist. Assoc. 81 (393), 82-86, 1986.
- [59] A. Tripathi, U. Singh and S.K. Singh, Estimation of $P (X< Y)$ for Gompertz distribution
based on upper records, Int. J. Model. Simul. 42 (3), 388-399, 2022.
- [60] H.R. Varian, A Bayesian approach to real estate assessment, in: Studies in Bayesian
Econometrics and Statistics in Honor of Leonard J. Savage, Eds. S.E. Fienberg and
A. Zellner, North-Holland Publishing Company, Amsterdam, 195-208, 1975.
- [61] L.A. Wasserman, All of Statistics: A Concise Course in Statistical Inference, New
York: Springer, 2004.
- [62] A.C.M. Wong, and Y.Y. Wu, A note on interval estimation of $P (X< Y)$ using lower
record data from the generalized exponential distribution, Comput. Statist. Data Anal.
53 (10), 3650-3658, 2009.
- [63] A. Zellner, Bayesian estimation and prediction using asymmetric loss functions, J.
Amer. Statist. Assoc. 81 (394), 446-451, 1986.