Year 2023,
, 768 - 784, 30.05.2023
Mehdi Bazyar
,
Einolah Deiri
,
Ezzatallah Baloui Jamkhaneh
References
- [1] H.H. Ahmad, Best prediction method for progressive type-II censored samples under
new Pareto model with applications, J. Math. 2021, Article ID 1355990, 2021.
- [2] A. Algarni, A.M. Almarashi, H. Okasha and H.K.T. Ng, E-Bayesian estimation of
Chen distribution based on type-I censoring scheme, Entropy 22, 636, 2020.
- [3] R. Alshenawy, A. Al-Alwan, E.M. Almetwally, A.Z. Afify and H.M. Almongy, Progressive
type-II censoring schemes of extended odd Weibull Exponential distribution with
applications in medicine and engineering, Mathematics 8 (10), 1–19, 2020.
- [4] M.N. Asl, R.A. Belaghi and H. Bevrani, Classical and Bayesian inferential approaches
using Lomax model under progressively type-I hybrid censoring, J. Comput. Appl.
Math. 343, 397–412, 2018.
- [5] M. Aslam, F. Noor and S. Ali, Shifted exponential distribution: Bayesian estimation,
prediction and expected test time under progressive censoring, J. Test. Eval. 48 (2),
1576–1593, 2020.
- [6] N. Balakrishnan and A. Sandhu, A simple simulation algorithm for generating progressive
type-II censored sample, Am. Stat. 49 (2), 229–230, 1995.
- [7] V.G. Cancho, F. Louzada-Neto and G.D. Barriga, The poisson-exponential lifetime
distribution, Comput. Stat. Data. Anal. 55 (1), 677–686, 2011.
- [8] A. Chaturvedi, B. Devi and and R. Gupta, Robust Bayesian analysis of Moore and
Bilikam family of lifetime distributions, Int. J. Agric. Stat. Sci. 15 (2), 497–522, 2019a.
- [9] A. Chaturvedi, S.-B. Kang and A. Malhotra, Preliminary test estimators and confidence
intervals for the parametric functions of the Moore and Bilikam family of lifetime
distributions based on records, Austrian J. Stat. 48 (4), 58–89, 2019b.
- [10] A.P. Dempster, N.M. Laird and D.B. Rubin, Maximum likelihood from incomplete
data via the EM algorithm, J. R. Stat. Soc. Series B. 39 (1), 1–38, 1977.
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a progressively censored generalized inverted exponential distribution, Stat. Methodol.
32, 185–202, 2016.
- [12] E.S.A. El-Sherpieny, E.M. Almetwally and H.Z. Muhammed Bayesian and non-
Bayesian estimation for the parameter of bivariate generalized Rayleigh distribution
based on clayton copula under progressive type-II censoring with random removal,
Sankhya A. 10.1007/s13171-021-00254-3, 2021.
- [13] M. Han, The structure of hierarchical prior distribution and its applications, Chin.
Operat. Res. Manage. Sci. 6 (3), 31–40, 1997.
- [14] P.W. Jones and S.K. Ashour, Bayesian estimation of the parameters of the mixed
exponential distribution from censored samples, Biom. J. 18 (8), 633–637, 2007.
- [15] A.H. Moore and J.E. Bilikam, Bayesian estimation of parameters of life distributions
and reliability from type II censored samples, IEEE Trans. Reliab. 27, 64–67, 1978.
- [16] N. Mukhopadhyay, A. Chaturvedi and A. Malhotra, Two-stage procedures for the
bounded risk point estimation of the parameter and hazard rate in two families of
distributions, Seq. Anal. 37 (1), 69–89, 2018.
- [17] A. Mustafa, B.S. Desouky and S. AL-Garash, The Weibull Generalized flexible Weibull
extension distribution, Data Sci. J. 14 (3), 453–478, 2017.
- [18] F.S. Nielsen, The stochastic EM algorithm: estimation and asymptotic results,
Bernoulli 6, 457–489, 2000.
- [19] A. Rabie and J. Li, E-Bayesian estimation based on Burr-X generalized type-II hybrid
censored data, Symmetry 11 (5), 626, 2019.
- [20] H.M. Reyad and A. So, Bayesian and E-Bayesian estimation for the Kumaraswamy
distribution based on type-II censoring, Int. j. adv. math. sci. 4 (1), 10–17, 2016.
- [21] S. Singh and Y.M. Tripathi, Estimating the parameters of an inverse Weibull distribution
under progressive type-I interval censoring, Stat. Pap. 59 (1), 21–56, 2018.
- [22] A.A. Soliman, Estimators for the finite mixture of Rayleigh model based on progressively
censored data, Commun. Stat.-Theory Methods. 35 (5), 803–820, 2006.
- [23] Q. Yin and H. Liu, Bayesian estimation of geometric distribution parameter under
the scaled squared error loss function, IEEE Int. Environ. Sci. and Inf. Appl. Technol.
2010, 650–653, 2010.
The Moore and Bilikam model and Burr XII sub-model under progressively type-II censoring scheme
Year 2023,
, 768 - 784, 30.05.2023
Mehdi Bazyar
,
Einolah Deiri
,
Ezzatallah Baloui Jamkhaneh
Abstract
The Moore and Bilikam family includes lifetime distributions, hence there is a need for a meticulous investigation of the proposed family. We evaluate different estimation procedures for both parameters and reliability function of the Moore and Bilikam family comprehensively, including the maximum likelihood, Bayesian and E-Bayesian estimation methods. The estimation methods of the Moore and Bilikam family are compared via the simulation data, whereas simulation results of the Burr XII sub-model are reported. Based on the simulation approach, we concluded the estimates of the Moore and Bilikam family are convergent to the corresponding parameters, and the root mean square error values derived by the E-Bayesian method are less than other estimators. The analysis of the time between failures of secondary reactor pumps data set has been represented for illustrative purposes, which confirmed simulation results.
References
- [1] H.H. Ahmad, Best prediction method for progressive type-II censored samples under
new Pareto model with applications, J. Math. 2021, Article ID 1355990, 2021.
- [2] A. Algarni, A.M. Almarashi, H. Okasha and H.K.T. Ng, E-Bayesian estimation of
Chen distribution based on type-I censoring scheme, Entropy 22, 636, 2020.
- [3] R. Alshenawy, A. Al-Alwan, E.M. Almetwally, A.Z. Afify and H.M. Almongy, Progressive
type-II censoring schemes of extended odd Weibull Exponential distribution with
applications in medicine and engineering, Mathematics 8 (10), 1–19, 2020.
- [4] M.N. Asl, R.A. Belaghi and H. Bevrani, Classical and Bayesian inferential approaches
using Lomax model under progressively type-I hybrid censoring, J. Comput. Appl.
Math. 343, 397–412, 2018.
- [5] M. Aslam, F. Noor and S. Ali, Shifted exponential distribution: Bayesian estimation,
prediction and expected test time under progressive censoring, J. Test. Eval. 48 (2),
1576–1593, 2020.
- [6] N. Balakrishnan and A. Sandhu, A simple simulation algorithm for generating progressive
type-II censored sample, Am. Stat. 49 (2), 229–230, 1995.
- [7] V.G. Cancho, F. Louzada-Neto and G.D. Barriga, The poisson-exponential lifetime
distribution, Comput. Stat. Data. Anal. 55 (1), 677–686, 2011.
- [8] A. Chaturvedi, B. Devi and and R. Gupta, Robust Bayesian analysis of Moore and
Bilikam family of lifetime distributions, Int. J. Agric. Stat. Sci. 15 (2), 497–522, 2019a.
- [9] A. Chaturvedi, S.-B. Kang and A. Malhotra, Preliminary test estimators and confidence
intervals for the parametric functions of the Moore and Bilikam family of lifetime
distributions based on records, Austrian J. Stat. 48 (4), 58–89, 2019b.
- [10] A.P. Dempster, N.M. Laird and D.B. Rubin, Maximum likelihood from incomplete
data via the EM algorithm, J. R. Stat. Soc. Series B. 39 (1), 1–38, 1977.
- [11] S. Dey, S. Singh, Y.M. Tripathi and A. Asgharzadeh, Estimation and prediction for
a progressively censored generalized inverted exponential distribution, Stat. Methodol.
32, 185–202, 2016.
- [12] E.S.A. El-Sherpieny, E.M. Almetwally and H.Z. Muhammed Bayesian and non-
Bayesian estimation for the parameter of bivariate generalized Rayleigh distribution
based on clayton copula under progressive type-II censoring with random removal,
Sankhya A. 10.1007/s13171-021-00254-3, 2021.
- [13] M. Han, The structure of hierarchical prior distribution and its applications, Chin.
Operat. Res. Manage. Sci. 6 (3), 31–40, 1997.
- [14] P.W. Jones and S.K. Ashour, Bayesian estimation of the parameters of the mixed
exponential distribution from censored samples, Biom. J. 18 (8), 633–637, 2007.
- [15] A.H. Moore and J.E. Bilikam, Bayesian estimation of parameters of life distributions
and reliability from type II censored samples, IEEE Trans. Reliab. 27, 64–67, 1978.
- [16] N. Mukhopadhyay, A. Chaturvedi and A. Malhotra, Two-stage procedures for the
bounded risk point estimation of the parameter and hazard rate in two families of
distributions, Seq. Anal. 37 (1), 69–89, 2018.
- [17] A. Mustafa, B.S. Desouky and S. AL-Garash, The Weibull Generalized flexible Weibull
extension distribution, Data Sci. J. 14 (3), 453–478, 2017.
- [18] F.S. Nielsen, The stochastic EM algorithm: estimation and asymptotic results,
Bernoulli 6, 457–489, 2000.
- [19] A. Rabie and J. Li, E-Bayesian estimation based on Burr-X generalized type-II hybrid
censored data, Symmetry 11 (5), 626, 2019.
- [20] H.M. Reyad and A. So, Bayesian and E-Bayesian estimation for the Kumaraswamy
distribution based on type-II censoring, Int. j. adv. math. sci. 4 (1), 10–17, 2016.
- [21] S. Singh and Y.M. Tripathi, Estimating the parameters of an inverse Weibull distribution
under progressive type-I interval censoring, Stat. Pap. 59 (1), 21–56, 2018.
- [22] A.A. Soliman, Estimators for the finite mixture of Rayleigh model based on progressively
censored data, Commun. Stat.-Theory Methods. 35 (5), 803–820, 2006.
- [23] Q. Yin and H. Liu, Bayesian estimation of geometric distribution parameter under
the scaled squared error loss function, IEEE Int. Environ. Sci. and Inf. Appl. Technol.
2010, 650–653, 2010.