Classical and Bayesian estimations of improved Weibull-Weibull distribution for complete and censored failure times data

被引:7
|
作者
Wang, Hong [1 ]
Abba, Badamasi [1 ,2 ]
Pan, Jianxin [3 ,4 ]
机构
[1] Cent South Univ, Sch Math & Stat, Changsha, Peoples R China
[2] Yusuf Maitama Sule Univ, Dept Math, Fac Sci, Kano, Nigeria
[3] Beijing Normal Univ, Res Ctr Math, Zhuhai 519087, Peoples R China
[4] BNU HKBU United Int Coll, Guangdong Prov Key Lab Interdisciplinary Res & Ap, Zhuhai 519087, Peoples R China
关键词
bathtub-shaped failure rate; Bayesian inference; lifetime data analysis; maximum likelihood method; Weibull-Weibull distribution; BATHTUB; MODEL; EXTENSION; PREDICTION; FAMILY;
D O I
10.1002/asmb.2698
中图分类号
C93 [管理学]; O22 [运筹学];
学科分类号
070105 ; 12 ; 1201 ; 1202 ; 120202 ;
摘要
In this article, we demonstrate how to enhance the Weibull-Weibull (WW) distribution introduced in the earlier literature into a better form for fitting monotone and non-monotone failure rate data, especially the bathtub-shaped failure rate data with or without a flat region. The model is referred to as an improved WW distribution. The model's flexibility enables it to describe lifetime data with various failure rate functions, including increasing, decreasing, U or V-shaped, and bathtub-shaped with a comparatively low and long-flat segment. We provide a thorough Bayesian analysis of the modified model for complete and right-censored data. Additionally, we developed maximum likelihood estimators for the model's parameters for both complete and right-censored data. The Bayesian credible and asymptotic confidence intervals of the estimators are defined, and simulation results validate the estimators' consistency. To illustrate the applications of the improved distribution with the WW and other generalized distributions, we apply one censored and one uncensored failure times data, each with bathtub-shaped failure rates. The numerical results demonstrate that the improved WW model outperforms the WW distribution and other existing models, as indicated by goodness-of-fit statistics and supported by the fitted models' survival and failure rate curves and P-P plots.
引用
收藏
页码:997 / 1018
页数:22
相关论文
共 50 条
  • [21] Limited failure-censored life test for the Weibull distribution
    Wu, JW
    Tsai, TR
    Ouyang, LY
    [J]. IEEE TRANSACTIONS ON RELIABILITY, 2001, 50 (01) : 107 - 111
  • [22] The fracture load and failure types of veneered anterior zirconia crowns: An analysis of normal and Weibull distribution of complete and censored data
    Stawarczyk, Bogna
    Oezcan, Mutlu
    Haemmerle, Christoph H. F.
    Roos, Malgorzata
    [J]. DENTAL MATERIALS, 2012, 28 (05) : 478 - 487
  • [23] Bayesian Estimations of Shannon Entropy and Renyi Entropy of Inverse Weibull Distribution
    Ren, Haiping
    Hu, Xue
    [J]. MATHEMATICS, 2023, 11 (11)
  • [24] Regression modelling of interval-censored failure time data using the Weibull distribution
    Scallan, AJ
    [J]. JOURNAL OF APPLIED STATISTICS, 1999, 26 (05) : 613 - 618
  • [25] ON BAYESIAN ANALYSIS OF RIGHT CENSORED WEIBULL DISTRIBUTION USING APPROXIMATE METHODS
    Feroze, Navid
    Aslam, Muhammad
    Raftab, Mariya
    Abbasi, Bilal Ahmed
    [J]. JOURNAL OF RELIABILITY AND STATISTICAL STUDIES, 2018, 11 (02): : 193 - 217
  • [27] Bayes Interval Estimation on the Parameters of the Weibull Distribution for Complete and Censored Tests
    Motaei, A.
    Niaki, S. T. A.
    Fard, N.
    [J]. INTERNATIONAL JOURNAL OF ENGINEERING, 2013, 26 (09): : 985 - 996
  • [28] MAXIMUM LIKELIHOOD ESTIMATION IN WEIBULL DISTRIBUTION BASED ON COMPLETE AND ON CENSORED SAMPLE
    COHEN, AC
    [J]. ANNALS OF MATHEMATICAL STATISTICS, 1965, 36 (01): : 354 - &
  • [29] Bayesian Using Extension Jeffreys Prior for Weibull Regression Censored Data
    Ahmed, Al Omari Mohammed
    [J]. INTERNATIONAL JOURNAL OF APPLIED MATHEMATICS & STATISTICS, 2018, 57 (06): : 73 - 82
  • [30] A Simulation of Data Censored Rigth Type I with Weibull Distribution
    Gaspar, Daniel
    Ferreira, Luis Andrande
    [J]. 2022 6TH INTERNATIONAL CONFERENCE ON SYSTEM RELIABILITY AND SAFETY, ICSRS, 2022, : 505 - 511