Basu-Dhar bivariate geometric distribution in the presence of covariates and censored data: a Bayesian approach

被引：6
作者：
Achcar, J. A. [1 ]
Davarzani, N. [2 ]
Souza, R. M. [3 ]
机构：
[1] Univ Sao Paulo, Fac Med Ribeirao Preto, Dept Social Med, Ribeirao Preto, SP, Brazil
[2] Maastricht Univ, Dept Knowledge Engn, NL-6200 MD Maastricht, Netherlands
[3] Fed Technol Univ Parana, Dept Math, Cornelio Procopio, Parana, Brazil
来源：
JOURNAL OF APPLIED STATISTICS | 2016年 / 43卷 / 09期
关键词：
Discrete bivariate lifetime data; Basu-Dhar geometric distribution; censored data; covariates; EXPONENTIAL-DISTRIBUTION; RELIABILITY; REGRESSION; EXTENSION; INFERENCE; BLOCK;
D O I：
10.1080/02664763.2015.1117589
中图分类号：
O21 [概率论与数理统计]; C8 [统计学];
学科分类号：
020208 ; 070103 ; 0714 ;
摘要：
In this paper, we introduce classical and Bayesian approaches for the Basu-Dhar bivariate geometric distribution in the presence of covariates and censored data. This distribution is considered for the analysis of bivariate lifetime as an alternative to some existing bivariate lifetime distributions assuming continuous lifetimes as the Block and Basu or Marshall and Olkin bivariate distributions. Maximum likelihood and Bayesian estimators are presented. Two examples are considered to illustrate the proposed methodology: an example with simulated data and an example with medical bivariate lifetime data.
引用
收藏
页码：1636 / 1648
页数：13
相关论文
共 50 条
[31]   A new approach to modeling the cure rate in the presence of interval censored data [J].
Pal, Suvra ;
Peng, Yingwei ;
Aselisewine, Wisdom .
COMPUTATIONAL STATISTICS, 2024, 39 (05) :2743-2769
[32]   Asymmetric Randomly Censored Mortality Distribution: Bayesian Framework and Parametric Bootstrap with Application to COVID-19 Data [J].
EL-Sagheer, Rashad M. ;
Eliwa, Mohamed S. ;
Alqahtani, Khaled M. ;
EL-Morshedy, Mahmoud .
JOURNAL OF MATHEMATICS, 2022, 2022
[33]   Bayesian and maximum likelihood inference approaches for the discrete generalized Sibuya distribution with censored data [J].
de Freitas, Bruno Caparroz Lopes ;
Peres, Marcos Vinicius de Oliveira ;
Achcar, Jorge Alberto ;
Martinez, Edson Zangiacomi .
ELECTRONIC JOURNAL OF APPLIED STATISTICAL ANALYSIS, 2022, 15 (01) :50-74
[34]   Bayesian multiple change-point estimation for exponential distribution with truncated and censored data [J].
He, Chaobing .
COMMUNICATIONS IN STATISTICS-THEORY AND METHODS, 2017, 46 (12) :5827-5839
[35]   Modelling dependence structures of extreme wind speed using bivariate distribution: a Bayesian approach [J].
Diriba, Tadele Akeba ;
Debusho, Legesse Kassa ;
Botai, Joel Ondego .
ENVIRONMENTAL AND ECOLOGICAL STATISTICS, 2020, 27 (02) :319-362
[36]   A bivariate distribution for the reliability analysis of failure data in presence of a forewarning or primer event [J].
Pulcini, G. .
COMMUNICATIONS IN STATISTICS-THEORY AND METHODS, 2006, 35 (11) :2107-2126
[37]   A Bayesian approach for reliability estimation for non-homogeneous and interval-censored failure data [J].
da Cunha, Beatriz Sales ;
Moura, Marcio das Chagas ;
Azevedo, Rafael ;
Santana, Joao Mateus Marques ;
Maior, Caio Bezerra Souto ;
Lins, Isis Didier ;
Mendes, Renato ;
Lima, Everton Nogueira ;
Lucas, Thais Campos ;
Siqueira, Paulo Gabriel ;
de Negreiros, Ana Claudia Souza Vidal .
PROCESS SAFETY AND ENVIRONMENTAL PROTECTION, 2024, 182 :775-788
[38]   Variational Bayesian approach for analyzing interval-censored data under the proportional hazards model [J].
Liu, Wenting ;
Li, Huiqiong ;
Tang, Niansheng ;
Lyu, Jun .
COMPUTATIONAL STATISTICS & DATA ANALYSIS, 2024, 195
[39]   Classical and Bayesian estimations of improved Weibull-Weibull distribution for complete and censored failure times data [J].
Wang, Hong ;
Abba, Badamasi ;
Pan, Jianxin .
APPLIED STOCHASTIC MODELS IN BUSINESS AND INDUSTRY, 2022, 38 (06) :997-1018
[40]   Reliability analysis for Weibull distribution with homogeneous heavily censored data based on Bayesian and least-squares methods [J].
Jia, Xiang .
APPLIED MATHEMATICAL MODELLING, 2020, 83 :169-188
12345