Accurate computation of single and product moments of order statistics under progressive censoring

An accurate procedure is proposed to calculate approximate moments of progressive order statistics in the context of statistical inference for lifetime models. The study analyses the performance of power series expansion to approximate the moments for location and scale distributions with high precision and smaller deviations with respect to the exact values. A comparative analysis between exact and approximate methods is shown using some tables and figures. The different approximations are applied in two situations. First, we consider the problem of computing the large sample variance–covariance matrix of maximum likelihood estimators. We also use the approximations to obtain progressively censored sampling plans for log-normal distributed data. These problems illustrate that the presented procedure is highly useful to compute the moments with precision for numerous censoring patterns and, in many cases, is the only valid method because the exact calculation may not be applicable.     

Progressive censoring with fixed censoring times

In this paper, we revisit the progressive Type-I censoring scheme as it has originally been introduced by Cohen [Progressively censored samples in life testing. Technometrics. 1963;5(3):327–339]. In fact, original progressive Type-I censoring proceeds as progressive Type-II censoring but with fixed censoring times instead of failure time based censoring times. Apparently, a time truncation has been added to this censoring scheme by interpreting the final censoring time as a termination time. Therefore, not much work has been done on Cohens's original progressive censoring scheme with fixed censoring times. Thus, we discuss distributional results for this scheme and establish exact distributional results in likelihood inference for exponentially distributed lifetimes. In particular, we obtain the exact distribution of the maximum likelihood estimator (MLE). Further, the stochastic monotonicity of the MLE is verified in order to construct exact confidence intervals for both the scale parameter and the reliability.     

Inference and optimal design of multiple constant-stress testing for generalized half-normal distribution under type-II progressive censoring

The generalized half-normal (GHN) distribution and progressive type-II censoring are considered in this article for studying some statistical inferences of constant-stress accelerated life testing. The EM algorithm is considered to calculate the maximum likelihood estimates. Fisher information matrix is formed depending on the missing information law and it is utilized for structuring the asymptomatic confidence intervals. Further, interval estimation is discussed through bootstrap intervals. The Tierney and Kadane method, importance sampling procedure and Metropolis-Hastings algorithm are utilized to compute Bayesian estimates. Furthermore, predictive estimates for censored data and the related prediction intervals are obtained. We consider three optimality criteria to find out the optimal stress level. A real data set is used to illustrate the importance of GHN distribution as an alternative lifetime model for well-known distributions. Finally, a simulation study is provided with discussion.     

站在人类先进文化发展的潮头

该文以唯物史观为指导,阐明了马克思主义文化理论、中国现代文化的形成和中国先进文化的发展方向.作者认为文化是人类社会在经济、政治、精神上的反映,包括意识形态和其他一切精神活动及其产物,对经济、政治又具有强大的反作用.中国现代社会主义文化是由农业封建主义文化在近百年的经济、政治发展的基础上逐渐演变而成的,它的前进方向是面向现代化、面向世界、面向未来的民族的、科学的、大众的社会主义文化.     

刚体转动渐进跟踪控制的逆系统方法

逆系统方法是以非线性控制为目的,以直接分析为途径,以动态系统的逆概念为核心。该文将逆系统方法应用于刚体动力学中,运用非线性控制的逆系统方法设计Euler动力学方程的控制器,通过对一个陀螺的外力矩进行实施控制,使刚体在动坐标系下的角速度稳定跟踪指令,来实现对刚体转动的渐进跟踪控制。     

知识型企业结构、特征及报酬递增效应分析

在市场经济条件下,知识已经成为企业竞争力的源泉.知识经济、知识管理、知识型企业等思想被越来越多的人所接受.和传统企业相比,知识型企业的结构及特征有它特定的一面.文章在分析知识型企业内外部结构的基础上,对知识型企业的特征进行了分析,进而探讨了由其特征所决定的知识型企业生产函数及报酬递增效应.     

试论“思想家的小说”的作者吴敬梓的思想

吴敬梓的思想内涵十分丰赡 ,传统思想中的儒家思想和魏晋六朝风尚对他的影响至大 ,而时代思潮中的颜李学说以及自然科学学风也同样影响了他。吴敬梓之所以受到这些思想的影响 ,是与他的家庭传统和生活实践密切相关的。而研究他的思想必须从他所创造的艺术形象着手 ,重视形象思维的特性。     

Accelerated life test sampling plans for the Weibull distribution under Type I progressive interval censoring with random removals

This paper considers the design of accelerated life test (ALT) sampling plans under Type I progressive interval censoring with random removals. We assume that the lifetime of products follows a Weibull distribution. Two levels of constant stress higher than the use condition are used. The sample size and the acceptability constant that satisfy given levels of producer's risk and consumer's risk are found. In particular, the optimal stress level and the allocation proportion are obtained by minimizing the generalized asymptotic variance of the maximum likelihood estimators of the model parameters. Furthermore, for validation purposes, a Monte Carlo simulation is conducted to assess the true probability of acceptance for the derived sampling plans.     

Likelihood estimation for a general class of inverse exponentiated distributions based on complete and progressively censored data

In this paper, we establish the existence and uniqueness of the maximum-likelihood estimates of the parameters of a general class of inverse exponentiated distributions based on complete as well as progressively Type-I and Type-II censored data.     

Inference for Weibull distribution under adaptive Type-I progressive hybrid censored competing risks data

In this paper, a competing risks model is considered under adaptive type-I progressive hybrid censoring scheme (AT-I PHCS). The lifetimes of the latent failure times have Weibull distributions with the same shape parameter. We investigate the maximum likelihood estimation of the parameters. Bayes estimates of the parameters are obtained based on squared error and LINEX loss functions under the assumption of independent gamma priors. We propose to apply Markov Chain Monte Carlo (MCMC) techniques to carry out a Bayesian estimation procedure and in turn calculate the credible intervals. To evaluate the performance of the estimators, a simulation study is carried out.