Likelihood Inference under Generalized Hybrid Censoring Scheme with Comp eting Risks

Statistical inference is developed for the analysis of generalized type-II hybrid censoring data under exponential competing risks model. In order to solve the problem that approximate methods make unsatisfactory performances in the case of small sample size, we establish the exact conditional distributions of estimators for parameters by conditional moment generating function(CMGF). Furthermore, confidence intervals(CIs) are constructed by exact distributions, approximate distributions as well as bootstrap method respectively, and their performances are evaluated by Monte Carlo simulations. And finally, a real data set is analyzed to illustrate all the methods developed here.     

Statistical Inference for the Rayleigh distribution under progressively Type-II censoring with binomial removal

This paper takes into account the estimation for the unknown parameter of the Rayleigh distribution under Type II progressive censoring with binomial removals, where the number of units removed at each failure time follows a binomial distribution. Maximum likelihood and Bayes procedure are used to derive both point and interval estimates of the parameters involved in the model. The expected termination point to complete the censoring test is computed and analyzed under binomial censoring scheme. Numerical examples are given to illustrate the approach by means of Monte Carlo simulation. A real life data set is used for illustrative purposes in conclusion.     

广义指数分布下恒定应力加速寿命试验的贝叶斯分析

研究产品寿命服从广义指数分布的有关加速寿命试验的贝叶斯统计分析.首先介绍了广义指数分布在恒定应力下的加速寿命试验基本过程;其次在完全样本,和定数截尾样本下,分别给出了广义指数分布参数的贝叶斯估计;最后运用随机模拟方法对各种估计结果的优良性进行了分析比较.     

Statistical analysis of progressive stress accelerated life test for the product of two-parameter Laplace BS fatigue life distribution under inverse power law model

Based on the product of two-parameter Laplace Birnbaum-Saunders fatigue life distribution, its failure distribution mode is theoretically derived under the progressive stress accelerated life test with inverse power law model, and then three-parameter generalized Laplace Birnbaum-Saunders fatigue life distribution is introduced. The basic properties of three-parameter generalized Laplace Birnbaum-Saunders fatigue life distribution are analyzed, and the image characteristics of its density function, failure rate function and average failure rate function are investigated. Meanwhile, the point estimate method is given for three parameters, and then the point estimates of parameters are obtained for the product of two-parameter Laplace Birnbaum-Saunders fatigue life distribution under the progressive stress accelerated life test with inverse power law model. In addition, the practical example and simulation examples are illustrated to show the feasibility of the proposed method.     

Statistical Analysis in Constant-Stress Accelerated Life Tests for Generalized Exponential Distribution Based on Adaptive Type-II Progressive Hybrid Censored Data

Based on adaptive type-II progressive hybrid censored data statistical analysis for constant-stress accelerated life test (CS-ALT) with products' lifetime following two-parameter generalized exponential (GE) distribution is investigated. The estimates of the unknown parameters and the reliability function are obtained through a new method combining the EM algorithm and the least square method. The observed Fisher information matrix is achieved with missing information principle, and the asymptotic unbiased estimate (AUE) of the scale parameter is also obtained. Confidence intervals (CIs) for the parameters are derived using asymptotic normality of the estimators and the percentile bootstrap (Boot-p) method. Finally, Monte Carlo simulation study is carried out to investigate the precision of the point estimates and interval estimates, respectively. It is shown that the AUE of the scale parameter is better than the corresponding two-step estimation, and the Boot-p CIs are more accurate than the corresponding asymptotic CIs.     

���ɾʧ�����»��ָ���ֲ��Ĺ���

The hybrid censoring scheme is a mixture of type-I and type-II censoring schemes. It is a popular censoring scheme in the literature of life data analysis. Mixed exponential distribution (MED) models is a class of favorable models in reliability statistics. Nevertheless, there is no much discussion to focus on parameters estimation for MED models with hybrid censored samples. We will address this problem in this paper. The EM (Expectation-Maximization) algorithm is employed to derive the closed form of the maximum likelihood estimators (MLEs). Finally, Monte Carlo simulations and a real-world data analysis are conducted to illustrate the proposed method.     

Generalized MLE of a Joint Distribution Function with Multivariate Interval-Censored Data

We consider the problem of estimation of a joint distribution function of a multivariate random vector with interval-censored data. The generalized maximum likelihood estimator of the distribution function is studied and its consistency and asymptotic normality are established under the case 2 multivariate interval censorship model and discrete assumptions on the censoring random vectors.     

A simulation-based approach to the study of coefficient of variation of Gompertz distribution under progressive first-failure censoring

In applied statistics, the coefficient of variation is widely used. However, inference concerning the coefficient of variation of non-normal distributions are rarely reported. In this article, a simulation-based Bayesian approach is adopted to estimate the coefficient of variation (CV) under progressive first-failure censored data from Gompertz distribution. The sampling schemes such as, first-failure censoring, progressive type II censoring, type II censoring and complete sample can be obtained as special cases of the progressive first-failure censored scheme. The simulation-based approach will give us a point estimate as well as the empirical sampling distribution of CV. The joint prior density as a product of conditional gamma density and inverted gamma density for the unknown Gompertz parameters are considered. In addition, the results of maximum likelihood and parametric bootstrap techniques are also proposed. An analysis of a real life data set is presented for illustrative purposes. Results from simulation studies assessing the performance of our proposed method are included.     

Statistical Analysis Technique of Two-parameter Generalized Exponential Sum Distribution

A new life distribution is proposed, known as ``two-parameter generalized exponential sum distribution". We study the density function and failure rate function, the average failure rate function, the image features and the numerical characteristics of the mean residual life of the distribution. Several methods of calculating point estimation of parameters are discussed. Through the Monte-Carlo simulation, we compare the precision of the point estimations. In our opinion, the best linear unbiased estimation is the most optimal solution of these methods. At the same time, several methods of calculating parameters of interval estimations are given. We also discuss the precision of interval estimations by Monte-Carlo simulation and use the best linear unbiased estimation and the best linear invariant estimation to construct interval estimations which are better than other estimation method. Finally, several simulation examples and a case of maintaining tanks is used to illustrate the application of the methods presented in this paper.     

广义疲劳等寿命曲线与二维疲劳极限概率分布

基于传统等寿命曲线,提出了广义疲劳等寿命Sa-Sm曲线概念,并找出该曲线的普遍表达式;根据相关系数优化法建立了该表达式的参数估计公式,并给出了具有可靠度p的广义疲劳等寿命P-Sa-Sm曲线公式;以广义P-Sa-Sm曲线为基础,导出了二维疲劳极限概率分布;进行了3组不同应力均值下的LY11CZ铝合金材料的二维配对升降法试验,试验结果验证了广义疲劳等寿命Sa-Sm曲线的合理性和算法的拟合精度.