Marshall-Olkin exponential shock model covering all range of dependence

Bayesian analysis of three parameter singular Marshall-Olkin bivariate Pareto distribution

This paper provides bayesian analysis of singular Marshall-Olkin bivariate Pareto distribution. We consider three parameter singular Marshall-Olkin bivariate Pareto distribution. We consider two types of prior - reference prior and gamma prior. Bayes estimate of the parameters are calculated based on slice cum gibbs sampler and Lindley approximation. Credible interval is also provided for all methods and all prior distributions. A data analysis is kept for illustrative purpose.

Some variations of EM algorithms for Marshall-Olkin bivariate Pareto distribution with location and scale

Recently Asimit et. al used an EM algorithm to estimate Marshall-Olkin bivariate Pareto distribution. The distribution has seven parameters. We describe few alternative approaches of EM algorithm. A numerical simulation is performed to verify the performance of different proposed algorithms. A real-life data analysis is also shown for illustrative purposes.

Parameter Estimation of absolute continuous four parameter Geometric Marshall-Olkin bivariate Pareto Distribution

In this paper we formulate a four parameter absolute continuous Geometric Marshall-Olkin bivariate Pareto distribution and study its parameter estimation through EM algorithm and also explore the bayesian analysis through slice cum Gibbs sampler approach. Numerical results are shown to verify the performance of the algorithms. We illustrate the procedures through a real life data analysis.

Bayesian analysis of absolute continuous Marshall-Olkin bivariate Pareto distribution with location and scale parameters

This paper provides two different novel approaches of slice sampling to estimate the parameters of absolute continuous Marshall-Olkin bivariate Pareto distribution with location and scale parameters. We carry out the bayesian analysis taking gamma prior for shape and scale parameters and truncated normal for location parameters. Credible intervals and coverage probabilities are also provided for all methods. A real-life data analysis is shown for illustrative purpose.

Optimal B-Robust Estimation for the Parameters of Marshall-Olkin Extended Burr XII Distribution and Application for Modeling Data from Pharmacokinetics Study

Marshall-Olkin Extended Burr XII (MOEBXII) distribution family, which is a generalization of Burr XII distribution proposed by Al-Saiari et al. [1] , is a flexible distribution that can be used in many fields such as actuarial science, economics, life testing, reliability and failure time modeling. The parameters of the MOEBXII distribution are usually estimated by the maximum likelihood (ML) and least squares (LS) estimation methods. However, these estimators are not robust to the outliers which are often encountered in practice. There are two main purposes of this paper. The first one is to …

贝叶斯缺陷马尔可夫-奥林戈姆佩茨模型：一种识别治愈分数的综合方法

Bayesian defective Marshall-Olkin Gompertz model: an integrated approach to identifying cure fraction

本文提出一种贝叶斯缺陷回归模型，用于长期生存结果，利用马尔可夫-奥林戈姆佩茨分布，通过蒙特卡洛研究评估其渐近性质，并应用睾丸癌患者数据展示治愈分数的不确定性估计。