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As a new reliability test plan, generalized progressive hybrid censoring can improve test efficiency by allowing experimenters to observe a pre-specified number of failure samples before the final termination point. Based on a class of widely used life distribution in life data analysis --- generalized exponential distribution, this paper discusses its parameters inference issue under generalized progressive hybrid censoring scheme. EM Algorithm is used to estimate parameters of the considered model. Simulation studies and a real-data analysis are carried out to illustrate the performance of finite sample for the proposed procedure.     

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In this paper, we investigate a competing risks model based on exponentiated Weibull distribution under Type-I progressively hybrid censoring scheme. To estimate the unknown parameters and reliability function, the maximum likelihood estimators and asymptotic confidence intervals are derived. Since Bayesian posterior density functions cannot be given in closed forms, we adopt Markov chain Monte Carlo method to calculate approximate Bayes estimators and highest posterior density credible intervals. To illustrate the estimation methods, a simulation study is carried out with numerical results. It is concluded that the maximum likelihood estimation and Bayesian estimation can be used for statistical inference in competing risks model under Type-I progressively hybrid censoring scheme.     

Generalized Waiting Time Problems Associated with Pattern in Polya's Urn Scheme

Let X ₁, X ₂, ... be a sequence obtained by Polya's urn scheme. We consider a waiting time problem for the first occurrence of a pattern in the sequence X ₁, X ₂, ... , which is generalized by a notion score. The main part of our results is derived by the method of generalized probability generating functions. In Polya's urn scheme, the system of equations is composed of the infinite conditional probability generating functions, which can not be solved. Then, we present a new methodology to obtain the truncated probability generating function in a series up to an arbitrary order from the system of infinite equations. Numerical examples are also given in order to illustrate the feasibility of our results. Our results in this paper are not only new but also a first attempt to treat the system of infinite equations.     

自适应逐步II型混合截尾恒加寿命试验下广义指数分布的统计分析

在自适应逐步II型混合截尾恒定应力加速寿命试验下,讨论了两参数广义指数分布的统计分析。利用EM算法和最小二乘法相结合的新方法推导出未知参数与可靠度函数的点估计,通过信息缺失原则得到了观测Fisher信息阵和尺度参数的渐近无偏估计。利用估计的渐近正态性和参数bootstrap方法构造了参数的置信区间。最后运用Monte-Carlo方法分别对得到的点估计和区间估计的精度进行研究,结果表明尺度参数的渐近无偏估计优于相应的两步估计, Boot-p置信区间比相应的渐近置信区间更精确。     

具有多合同的广义加权保费的信度估计(英文)

本文讨论了广义加权保费原理下的信度估计,并把结论推广到多合同模型.通过概率分布的变换,本文得到了多合同模型下广义加权保费的非齐次和齐次信度估计.并且讨论了这些估计的统计性质.最后,运用重抽样方法讨论了信度因子中未知结构参数的估计.数值模拟表明,非齐次信度估计能运用于保险实际.     

Stochastic monotonicity of the MLE of exponential mean under different censoring schemes

In this paper, we present a general method which can be used in order to show that the maximum likelihood estimator (MLE) of an exponential mean θ is stochastically increasing with respect to θ under different censored sampling schemes. This propery is essential for the construction of exact confidence intervals for θ via “pivoting the cdf” as well as for the tests of hypotheses about θ. The method is shown for Type-I censoring, hybrid censoring and generalized hybrid censoring schemes. We also establish the result for the exponential competing risks model with censoring.