βExpectation and β-content tolerance intervals for dependent observations

Methods of constructing exact tolerance intervals (β-expectation and β-content) for independent observations are well known. For the case of dependent observations, obtaining exact results is not possible. In this article we provide an approximate method of constructing β-expectation tolerance intervals via a Taylor series expansion. Examples of independent observations are considered to compare the intervals constructed with those obtained by the exact method. For the case of non-stationary type processes we have proposed a method of constructing approximate β-content tolerance intervals. Once again an example is given to illustrate the results.     

Designs with Repeated Measurements on Any Number of Units over Varying Periods

In the usual repeated measurements designs (RMDs), the subjects are all observed for the same number of periods and the optimum RMDs require specified numbers of subjects, usually depending on the number of treatments to be used. In practice, it is sometimes not feasible to meet these requirements. To overcome this problem, alternative designs are suggested where any number of available subjects may be used and they may be observed for different periods. These designs are based on suitable serially balanced sequences which are shown to be optimal. Moreover, besides the usual direct and residual effects, the model considered has an extra term due to the interaction effect between them. The recommended designs are universally optimal in a very general class.     

Outlier Detection in Time Series Models Using Local Influence Method

We propose a new procedure for detecting a patch of outliers or influential observations for autoregressive integrated moving average (ARIMA) model using local influence analysis. It is shown that the dependency aspects of time series data gives rise to masking or smearing effects when the local influence analysis is performed using current perturbation schemes. We suggest a new perturbation scheme to take into account the dependent structure of time series data, and employ the stepwise local influence method to give a diagnostic procedure. We show that the new perturbation scheme can avoid the smearing effects, and the stepwise technique of local influence can successfully deal with masking effects. Various simulation studies are performed to show the efficiency of proposed methodology and a real example is used for illustrations.     

诗不厌改贵乎精也——简评许渊冲教授对“三美”的不断追求

大凡文学作品,其中包括诗歌,创作之初都会有所不足,需经反复修改才能不断完善,以臻完美。许渊冲教授是一位著名的古诗英译学者,凭他那译笔优美的诸多古诗英译本驰名中外。从他所提出的古诗英译中应具的“意美”、“音美”和“形美”三个方面着眼,通过对他先后出版的不同译本中的若干源于同一原诗的译诗进行分析比较,探索许渊冲教授对译诗反复修改、精益求精的执着精神,并以此论证他对“三美”的不断追求。     

Parameter Identification for Drift Fractional Brownian Motions with Application to the Chinese Stock Markets

This article deals with the problem of estimating all the unknown parameters in the drift fractional Brownian motion with discretely sampled data. The estimation procedure is built upon the marriage of the variation method and the ergodic theory. The strong consistencies of these estimators are provided. Moreover, our method and two existing approaches are compared based on the computational running time and the accuracy of estimation via simulation studies. We also apply the proposed method to the real high-frequency financial data within a window of 4 h in the trading day from the Chinese mainland stock market.     

论禁止重复诉讼的识别

禁止重复诉讼在减少被告二次应诉之烦、节约法院司法资源、避免造成矛盾判决等方面发挥着重要作用。禁止重复诉讼的识别标准主要有二要素说和三要素说,但多追求形式上的契合而忽视禁止重复诉讼的制度旨趣之根本。将不同学说中的各要素进行解构后再重构会发现,案件事实、诉讼标的和诉讼请求之间存在着多因一果或一因多果的关系,案件事实作为识别标准中的一个基础性要素,对纠纷的一次性解决之影响至巨。厘清案件事实的包含或分离关系,有助于判断后诉的提起是否构成重复诉讼。     

The two-sample problem with multivariate censored data: a new rank test family

A new rank test family is proposed to test the equality of two multivariate failure times distributions with censored observations. The tests are very simple: they are based on a transformation of the multivariate rank vectors to a univariate rank score and the resulting statistics belong to the familiar class of the weighted logrank test statistics. The new procedure is also applicable to multivariate observations in general, such as repeated measures, some of which may be missing. To investigate the performance of the proposed tests, a simulation study was conducted with bivariate exponential models for various censoring rates. The size and power of these tests against Lehmann alternatives were compared to the size and power of two other tests (Wei and Lachin, 1984 and Wei and Knuiman, 1987). In all simulations the new procedures provide a relatively good power and an accurate control over the size of the test. A real example from the National Cooperative Gallstone Study is given     

Dynamic risk control for project development

A statistical methodology for dynamic risk control is discussed. The research is aimed at constructing tools for the analysis of expert opinions within a company about the risks involved in the production of a new commercial product or service. Focus is on risk events and on the analysis of the expert assessments of probabilities, losses and correlations of such events. A rescoring loop of risk assessments and preventive actions taken by the company on the basis of these assessments is illustrated through an example on software development. Relevant literature on risk and subjective elicitations is reviewed.     

优化长株潭三市产业结构的对策研究

目前长株潭三市的产业结构存在着"同构化"、"低度化"、"低层次化"等诸多因素.加入WTO后,这些矛盾进一步存在将使长株潭三市经济面临更大的挑战,从而影响长株潭三市经济的发展,及时研究并确立相应的策略具有紧迫的现实意义.     

Efficient Covariance Estimation for Asynchronous Noisy High‐Frequency Data

Abstract. We focus on estimating the integrated covariance of log‐price processes in the presence of market microstructure noise. We construct a consistent asymptotically unbiased estimator for the quadratic covariation of two Itô processes in the case where high‐frequency asynchronous discrete returns under market microstructure noise are observed. This estimator is based on synchronization and multi‐scale methods and attains the optimal rate of convergence. A lower bound for the rate of convergence is derived from the local asymptotic normality property of the simpler parametric model with equidistant and synchronous observations. A Monte Carlo study analyses the finite sample size characteristics of our estimator.