威布尔分布场合步加试验和步降试验的效率比较分析

 本文通过大量的Monte-Carlo模拟,在四个不同的准则下就威布尔分布比较了步进应力加速寿命试验和步降应力加速寿命试验的效率,认为步降应力加速寿命试验很值得推广,尤其是针对耗损型产品。     

收入分配、技术进步与经济的持续增长——来自中国的经验

支撑中国经济近30年高增长的主要是要素投入而非技术进步,这种粗放型的增长方式以及这种方式下的经济增长都是不可持续的。中国经济发展正在进入"刘易斯转折区间",这可能为经济增长方式转变为主要依靠技术进步提供条件,也可能使经济进入均衡陷阱。技术进步本身有着内在的逻辑,它源于分工,而分工又具有自发演进的正反馈机制。建设"创新型国家"(或者说大范围的技术进步)难以依靠由政府动员全社会力量集中攻关的"举国体制"来实现,分工的深化才是技术进步,进而是经济持续增长的决定性因素。     

中国城乡发展动力结构调整的思考——收入分配视角的分析

近三十年来,中国经济实现了持续高速增长,但增长动力结构失衡。在投资、消费、净出口三大需求对国民经济发展的拉动中,消费率偏低是一个不争的事实。消费率,即消费需求在支出法国内生产总值中所占的比重,反映的是从长期考察的一个国家在其发展过程中所处的历史阶段,而不是短期内国家宏观和微观的经济运行情况。它的高低适中不能用宏观和微观经济运行情况来判定,而是要看其是否与国家或地方的经济发展方式和路径相适应。中国经济发展正处于消费率由低转高的历史阶段,中国消费率的上升是一个渐进的过程,需要从宏观上实现一系列的国民收入分配机理运行工程,即劳动收入的国家干预工程、要素收入的二次分配工程、扩大公共消费工程和加大财政转移支付工程。     

Bayesian inference for the parameters of Weibull distribution under progressive Type-I interval censored data with beta-binomial removals

This article considers the problem of estimating the parameters of Weibull distribution under progressive Type-I interval censoring scheme with beta-binomial removals. Classical as well as the Bayesian procedures for the estimation of unknown model parameters have been developed. The Bayes estimators are obtained under SELF and GELF using MCMC technique. The performance of the estimators, has been discussed in terms of their MSEs. Further, expression for the expected number of total failures has been obtained. A real dataset of the survival times for patients with plasma cell myeloma is used to illustrate the suitability of the proposed methodology.     

Effects of some design factors on the distribution of similarity indices in cluster analysis

This article investigates the effects of number of clusters, cluster size, and correction for chance agreement on the distribution of two similarity indices, namely, Jaccard and Rand indices. Skewness and kurtosis are calculated for the two indices and their corrected forms then compared with those of the normal distribution. Three clustering algorithms are implemented: complete linkage, Ward, and K-means. Data were randomly generated from bivariate normal distributions with specified means and variance covariance matrices. Three-way ANOVA is performed to assess the significance of the design factors using skewness and kurtosis of the indices as responses. Test statistics for testing skewness and kurtosis and observed power are calculated. Simulation results showed that independent of the clustering algorithms or the similarity indices used, the interaction effect cluster size x number of clusters and the main effects of cluster size and number of clusters were found always significant for skewness and kurtosis. The three way interaction of cluster size x correction x number of clusters was significant for skewness of Rand and Jaccard indices using all clustering algorithms, but was not significant using Ward's method for both Rand and Jaccard indices, while significant for Jaccard only using complete linkage and K-means algorithms. The correction for chance agreement was significant for skewness and kurtosis using Rand and Jaccard indices when complete linkage method is used. Hence, such design factors must be taken into consideration when studying distribution of such indices.     

Kiefer–Wolfowitz algorithm under quasi-associated random errors

In this article, we study the algorithm of Kiefer–Wolfowitz underquasi-associated random errors. We establish the complete convergence and obtain an exponential bound. Additionally, we build a confidence interval for the minimum. Numerical examples are sketched out to confirm the theoretical results and show the accuracy of the algorithm.     

Stochastic Bounds with a Low Rank Decomposition

We investigate how we can bound a discrete time Markov chain (DTMC) by a stochastic matrix with a low rank decomposition. In the first part of the article, we show the links with previous results for matrices with a decomposition of size 1 or 2. Then we show how the complexity of the analysis for steady-state and transient distributions can be simplified when we take into account the decomposition. Finally, we show how we can obtain a monotone stochastic upper bound with a low rank decomposition.     

Exact permutation inference for two sample repeated measures data

Experiments in which very few units are measured many times sometimes present particular difficulties. Interest often centers on simple location shifts between two treatment groups, but appropriate modeling of the error distribution can be challenging. For example, normality may be difficult to verify, or a single transformation stabilizing variance or improving normality for all units and all measurements may not exist. We propose an analysis of two sample repeated measures data based on the permutation distribution of units. This provides a distribution free alternative to standard analyses. The analysis includes testing, estimation and confidence intervals. By assuming a certain structure in the location shift model, the dimension of the problem is reduced by analyzing linear combinations of the marginal statistics. Recently proposed algorithms for computation of two sample permutation distributions, require only a few seconds for experiments having as many as 100 units and any number of repeated measures. The test has high asymptotic efficiency and good power with respect to tests based on the normal distribution. Since the computational burden is minimal, approximation of the permutation distribution is unnecessary.     

Distribution of linear combination of exponential variates

The exact distribution of a linear combination of n independent negative exponential random variables, when the coefficients of the linear combination are distinct and positive quantities, is well-known. This paper extends the above result to the general case, namely when the coefficients are arbitrary real numbers, positive or negative, distinct or coincident.