Survival analysis for a new compounded bivariate failure time distribution in shock and competing risk models via an EM algorithm
DOI10.1080/03610926.2019.1614193OpenAlexW2944906722WikidataQ127880522 ScholiaQ127880522MaRDI QIDQ5078014
Shirin Shoaee, Esmaile Khorram
Publication date: 20 May 2022
Published in: Communications in Statistics - Theory and Methods (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1080/03610926.2019.1614193
expectation-maximization algorithmGompertz distributioncompeting risks modelshock modelbivariate model
Multivariate distribution of statistics (62H10) Estimation in multivariate analysis (62H12) Exact distribution theory in statistics (62E15) Statistics (62-XX)
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Cites Work
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- On bivariate Weibull-geometric distribution
- Bivariate gamma-geometric law and its induced Lévy process
- The bivariate generalized linear failure rate distribution and its multivariate extension
- Estimating the parameters of the Marshall-Olkin bivariate Weibull distribution by EM algorithm
- On some lifetime distributions with decreasing failure rate
- A new class of bivariate distributions and its mixture
- Bivariate generalized exponential distribution
- Modified Sarhan-Balakrishnan singular bivariate distribution
- A vector multivariate hazard rate
- A lifetime distribution with decreasing failure rate
- The generalized modified Weibull power series distribution: theory and applications
- The compound class of extended Weibull power series distributions
- Test of fit for Marshall-Olkin distributions with applications
- Bivariate Survival Models for Coupled Lives
- The Weibull-geometric distribution
- How to Identify a Bathtub Hazard Rate
- Correlated Bivariate Sequences for Queueing and Reliability Applications
- Marshall–Olkin extended weibull distribution and its application to censored data
- A new method for adding a parameter to a family of distributions with application to the exponential and Weibull families
- Common Poisson Shock Models: Applications to Insurance and Credit Risk Modelling
- Families of Multivariate Distributions
- Parameter Estimation for Partially Complete Time and Type of Failure Data
- The exponentiated exponential–geometric distribution: a distribution with decreasing, increasing and unimodal failure rate
- A bivariate Pareto model
- Marshall–Olkin Extended Lomax Distribution and Its Application to Censored Data
- Some Concepts of Dependence
- A Multivariate Exponential Distribution
- Exponentiated Lomax Geometric Distribution: Properties and Applications
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