Likelihood‐based inference for a frailty‐copula model based on competing risks failure time data

[1]  Yimin Shi,et al.  Statistical analysis of dependent competing risks model in accelerated life testing under progressively hybrid censoring using copula function , 2015, Commun. Stat. Simul. Comput..

[2]  M. Kayid,et al.  Bivariate quantile residual life: a characterization theorem and statistical properties , 2019 .

[3]  D. Kundu,et al.  A bivariate Pareto model , 2014 .

[4]  Ahmed Raza,et al.  Maintenance Model of Digital Avionics , 2018 .

[5]  Ralf A. Wilke,et al.  A copula model for dependent competing risks , 2009 .

[6]  Hongwei Luo,et al.  Reliability Analysis of Multiple Causes of Failure in Presence of Independent Competing Risks , 2016, Qual. Reliab. Eng. Int..

[7]  Simon M. S. Lo,et al.  Competing Risks Copula Models for Unemployment Duration: An Application to a German Hartz Reform , 2015 .

[8]  A C Kimber,et al.  Dependent censoring in piecewise exponential survival models , 2015, Statistical methods in medical research.

[9]  Liying Wang,et al.  Reliability Research of Dependent Failure Systems Using Copula , 2014, Commun. Stat. Simul. Comput..

[10]  A. Nadas,et al.  The Distribution of the Identified Minimum of a Normal Pair Determines the Distribution of the Pair , 1971 .

[11]  ESTIMATION OF PARAMETERS OF MIXED EXPONENTIALLY DISTRIBUTED FAILURE TIME DISTRIBUTIONS FROM CENSORED LIFE TEST DATA , 1958 .

[12]  Jorge Alberto Achcar,et al.  The Lindley distribution applied to competing risks lifetime data , 2011, Comput. Methods Programs Biomed..

[13]  Xiao Liu,et al.  Planning of Accelerated Life Tests With Dependent Failure Modes Based on a Gamma Frailty Model , 2012, Technometrics.

[14]  T. Emura,et al.  Fitting competing risks data to bivariate Pareto models , 2019 .

[15]  Geert Ridder,et al.  The Non-Parametric Identification of Generalized Accelerated Failure-Time Models , 1990 .

[16]  Tsai-Hung Fan,et al.  Reliability Inference for a Copula-Based Series System Life Test Under Multiple Type-I Censoring , 2016, IEEE Transactions on Reliability.

[17]  Noël Veraverbeke,et al.  Generalized copula-graphic estimator , 2013 .

[18]  R. Arabi Belaghi,et al.  Estimation based on progressively type-I hybrid censored data from the Burr XII distribution , 2019 .

[19]  Yi-Hau Chen,et al.  Gene selection for survival data under dependent censoring: A copula-based approach , 2016, Statistical methods in medical research.

[20]  Hsiuying Wang,et al.  Approximate Tolerance Limits Under Log-Location-Scale Regression Models in the Presence of Censoring , 2010, Technometrics.

[21]  M. Steel,et al.  Incorporating unobserved heterogeneity in Weibull survival models: A Bayesian approach , 2017 .

[22]  Virginie Rondeau,et al.  Personalized dynamic prediction of death according to tumour progression and high-dimensional genetic factors: Meta-analysis with a joint model , 2018, Statistical methods in medical research.

[23]  I. W. Burr Cumulative Frequency Functions , 1942 .

[24]  N. Veraverbeke,et al.  Copula-graphic estimation with left-truncated and right-censored data , 2017 .

[25]  Takeshi Emura,et al.  A copula-based inference to piecewise exponential models under dependent censoring, with application to time to metamorphosis of salamander larvae , 2017, Environmental and Ecological Statistics.

[26]  Yili Hong,et al.  Prediction of remaining life of power transformers based on left truncated and right censored lifetime data , 2009, 0908.2901.

[27]  J. Lu,et al.  Some new constructions of bivariate Weibull models , 1990 .

[28]  Yan Shi,et al.  The copula-based method for statistical analysis of step-stress accelerated life test with dependent competing failure modes , 2019 .

[29]  Xingjian Wang,et al.  An accelerated life test model for solid lubricated bearings used in space based on time-varying dependence analysis of different failure modes , 2018, Acta Astronautica.

[30]  Takeshi Emura,et al.  Meta-analysis of individual patient data with semi-competing risks under the Weibull joint frailty–copula model , 2020, Comput. Stat..

[31]  Jayanta K. Ghosh,et al.  Identifiability of the multinormal and other distributions under competing risks model , 1978 .

[32]  Gabriel Escarela,et al.  Fitting competing risks with an assumed copula , 2003, Statistical methods in medical research.

[33]  Takeshi Emura,et al.  Likelihood-based inference for bivariate latent failure time models with competing risks under the generalized FGM copula , 2018, Comput. Stat..

[34]  Fu-Kwun Wang,et al.  EM algorithm for estimating the Burr XII parameters with multiple censored data , 2010, Qual. Reliab. Eng. Int..

[35]  John P. Klein,et al.  Estimates of marginal survival for dependent competing risks based on an assumed copula , 1995 .

[36]  Martin T. Wells,et al.  A Martingale Approach to the Copula-Graphic Estimator for the Survival Function under Dependent Censoring , 2001 .

[37]  Alan Watkins,et al.  An algorithm for maximum likelihood estimation in the three parameter Burr XII distribution , 1999 .

[38]  Virginie Rondeau,et al.  A joint frailty-copula model between tumour progression and death for meta-analysis , 2017, Statistical methods in medical research.

[39]  Jong-Hyeon Jeong,et al.  Cause-specific quantile residual life regression , 2017, Statistical methods in medical research.

[40]  M. L. Moeschberger,et al.  Life Tests Under Dependent Competing Causes of Failure , 1974 .

[41]  Tsai-Hung Fan,et al.  A Competing Risks Model With Multiply Censored Reliability Data Under Multivariate Weibull Distributions , 2019, IEEE Transactions on Reliability.