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Annals of Data Science
Published in: Annals of Data Science 2/2020

23-04-2020

Maximum Product Spacing Estimation of Weibull Distribution Under Adaptive Type-II Progressive Censoring Schemes

Authors: E. M. Almetwally, H. M. Almongy, M. K. Rastogi, M. Ibrahim

Published in: Annals of Data Science | Issue 2/2020

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Abstract

The adaptive type-II progressive censoring schemes of maximum product spacing will be discussed. This article discusses the estimation of the Weibull parameters using the maximum product spacing and the maximum likelihood estimation methods. We also discuss the construction of reliability estimation of adaptive type-II progressively censored reliability sampling schemes for the Weibull distribution to determine the optimal adaptive type-II progressive censoring schemes. The estimation is done under adaptive type-II progressive censored samples and a comparative study among the methods is made using Monte Carlo simulation. A real data is used to study the performance of the estimation process under this optimal scheme in practice.
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Literature
1.
Asgharzadeh A, Valiollahi R, Kundu D (2015) Prediction for future failures in Weibull distribution under hybrid censoring. J Stat Comput Simul 85(4):824–838CrossRef
2.
Jia X, Wang D, Jiang P, Guo B (2016) Inference on the reliability of Weibull distribution with multiply type-I censored data. Reliab Eng Syst Saf 150:171–181CrossRef
3.
Chandra N, Khan MA, Gopal G (2017) Optimum quadratic step-stress accelerated life test plan for Weibull distribution under type-I censoring. Int J Syst Assur Eng Manag 8(2):585–591CrossRef
4.
Nassar M, Abo-Kasem O, Zhang C, Dey S (2018) Analysis of Weibull distribution under adaptive type-II progressive hybrid censoring scheme. J Indian Soc Probab Stat 19(1):25–65CrossRef
5.
Almetwally EM, Almongy HM, El Sayed Mubarak. A (2018) Bayesian and maximum likelihood estimation for the Weibull generalized exponential distribution parameters using progressive censoring schemes. Pak J Stat Oper Res 14(4):853–868CrossRef
6.
Cheng RCH, Amin NAK (1979) Maximum product of spacings estimation with application to the lognormal distribution, Mathematics Report 79-1, University of Wales, Cardiff, Deptartment of Mathematics
7.
Cheng RCH, Amin NAK (1983) Estimating parameters in continuous univariate distributions with a shifted origin. J R Stat Soc Ser B Methodol 45(3):394–403
8.
Ranneby B (1984) The maximum spacing method. An estimation method related to the maximum likelihood method. Scand J Stat 11:93–112
9.
Singh U, Singh SK, Singh RK (2014) A comparative study of traditional estimation methods and maximum product spacings method in generalized inverted exponential distribution. J Stat Appl Probab 3(2):153CrossRef
10.
Almetwally EM, Almongy HM (2019) Estimation methods for the new Weibull–Pareto distribution: simulation and application. J Data Sci 17(3):610–630
11.
Ng HKT, Luo L, Hu Y, Duan F (2012) Parameter estimation of three-parameter Weibull distribution based on progressively type-II censored samples. J Stat Comput Simul 82(11):1661–1678CrossRef
12.
Kumar Singh R, Kumar Singh S, Singh U (2016) Maximum product spacings method for the estimation of parameters of generalized inverted exponential distribution under progressive type II censoring. J Stat Manag Syst 19(2):219–245CrossRef
13.
Basu S, Singh SK, Singh U (2018) Bayesian inference using product of spacings function for progressive hybrid type-I censoring scheme. Statistics 52(2):345–363CrossRef
14.
El-Sherpieny ESA, Almetwally EM, Muhammed HZ (2020) Progressive type-II hybrid censored schemes based on maximum product spacing with application to Power Lomax distribution. Stat Mech Appl, Physica A, p 124251
15.
Almetwally EM, Almongy HM (2019) Maximum product spacing and Bayesian method for parameter estimation for generalized power Weibull distribution under censoring scheme. J Data Sci 17(2):407–444
16.
Balakrishnan N, Ng HKT (2006) Precedence-type tests and applications. Wiley, HobokenCrossRef
17.
Balakrishnan N, Sandhu RA (1995) A simple simulation algorithm for generating progressively type-II censored samples. Am Stat 49:229–230
18.
Balakrishnan N (2007) Progressive censoring methodology: an appraisal (with discussions). TEST 16:211–296CrossRef
19.
Almetwaly EM, Almongy HM (2018) Estimation of the generalized power Weibull distribution parameters using progressive censoring schemes. Int J Probab Stat 7(2):51–61
20.
Almetwally EM, Almongy HM, Sabry MA (2019) Bayesian and classical estimation for the Weibull distribution parameters under progressive type-II censoring schemes. Int J Math Arch 10(7):6–22
21.
Ng HKT, Kundu D, Chan PS (2009) Statistical analysis of exponential lifetimes under an adaptive type-II progressive censoring scheme. Naval Res Logist (NRL) 56(8):687–698CrossRef
22.
Sobhi MMA, Soliman AA (2016) Estimation for the exponentiated Weibull model with adaptive type-II progressive censored schemes. Appl Math Model 40(2):1180–1192CrossRef
23.
Mahmoud MA, Soliman AA, Ellah AHA, El-Sagheer RM (2013) Estimation of generalized Pareto under an adaptive type-II progressive censoring. Intell Inf Manag 5(03):73
24.
Hemmati F, Khorram E (2017) On adaptive progressively type-II censored competing risks data. Commun Stat Simul Comput 46(6):4671–4693CrossRef
25.
Ateya SF, Mohammed HS (2017) Statistical inferences based on an adaptive progressive type-II censoring from exponentiated exponential distribution. J Egypt Math Soc 25(4):393–399CrossRef
26.
Almetwally EM, Almongy HM (2018) Estimation of the Marshall–Olkin extended Weibull distribution parameters under adaptive censoring schemes. Int J Math Arch 9(9):95–102
27.
Ismail AA (2014) Inference for a step-stress partially accelerated life test model with an adaptive type-II progressively hybrid censored data from Weibull distribution. J Comput Appl Math 260:533–542CrossRef
28.
Almetwally EM, Almongy HM, ElSherpieny EA (2019) Adaptive type-II progressive censoring schemes based on maximum product spacing with application of generalized Rayleigh distribution. J Data Sci 17(4):802–831
29.
Balakrishnan N, Aggarwala R (2000) Progressive censoring: theory, methods, and applications. Springer, BerlinCrossRef
30.
Lee ET, Wang J (2003) Statistical methods for survival data analysis, vol 476. Wiley, New YorkCrossRef
31.
Gupta RD, Kundu D (2003) Discriminating between Weibull and generalized exponential distributions. Comput Stat Data Anal 43(2):179–196CrossRef
Metadata
Title
Maximum Product Spacing Estimation of Weibull Distribution Under Adaptive Type-II Progressive Censoring Schemes
Authors
E. M. Almetwally
H. M. Almongy
M. K. Rastogi
M. Ibrahim
Publication date
23-04-2020
Publisher
Springer Berlin Heidelberg
Published in
Annals of Data Science / Issue 2/2020
Print ISSN: 2198-5804
Electronic ISSN: 2198-5812
DOI
https://doi.org/10.1007/s40745-020-00261-5

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