Improving the detection of unusual observations in high‐dimensional settings

Multivariate control charts are used to monitor stochastic processes for changes and unusual observations. Hotelling's T² statistic is calculated for each new observation and an out‐of‐control signal is issued if it goes beyond the control limits. However, this classical approach becomes unreliable as the number of variables p approaches the number of observations n, and impossible when p exceeds n. In this paper, we devise an improvement to the monitoring procedure in high‐dimensional settings. We regularise the covariance matrix to estimate the baseline parameter and incorporate a leave‐one‐out re‐sampling approach to estimate the empirical distribution of future observations. An extensive simulation study demonstrates that the new method outperforms the classical Hotelling T² approach in power, and maintains appropriate false positive rates. We demonstrate the utility of the method using a set of quality control samples collected to monitor a gas chromatography–mass spectrometry apparatus over a period of 67 days.     

论学校在学生伤害事故中的责任

近年来,学生伤害事故及其引发的法律纠纷越来越多,日益成为困扰学校工作的严重问题。文章在对学校与学生之间法律关系进行论述的基础上,结合相关法律规定,提出学校责任是一种过错责任及学校过错的判断标准,并分析了不同情况下学校承担责任的方式。     

FDR control of detected regions by multiscale matched filtering

Feature extraction from observed noisy samples is a common important problem in statistics and engineering. This paper presents a novel general statistical approach to the region detection problem in long data sequences. The proposed technique is a multiscale kernel regression in conjunction with statistical multiple testing for region detection while controlling the false discovery rate (FDR) and maximizing the signal-to-noise ratio via matched filtering. This is achieved by considering a one-dimensional region detection problem as its equivalent zero-dimensional peak detection problem. The detection method does not require a priori knowledge of the shape of the nonzero regions. However, if the shape of the nonzero regions is known a priori, e.g., rectangular pulse, the signal regions can also be reconstructed from the detected peaks, seen as their topological point representatives. Simulations show that the method can effectively perform signal detection and reconstruction in the simulated data under high noise conditions, while controlling the FDR of detected regions and their reconstructed length.     

On robustness of the Shiryaev–Roberts change-point detection procedure under parameter misspecification in the post-change distribution

The gist of the quickest change-point detection problem is to detect the presence of a change in the statistical behavior of a series of sequentially made observations, and do so in an optimal detection-speed-versus-“false-positive”-risk manner. When optimality is understood either in the generalized Bayesian sense or as defined in Shiryaev's multi-cyclic setup, the so-called Shiryaev–Roberts (SR) detection procedure is known to be the “best one can do”, provided, however, that the observations’ pre- and post-change distributions are both fully specified. We consider a more realistic setup, viz. one where the post-change distribution is assumed known only up to a parameter, so that the latter may be misspecified. The question of interest is the sensitivity (or robustness) of the otherwise “best” SR procedure with respect to a possible misspecification of the post-change distribution parameter. To answer this question, we provide a case study where, in a specific Gaussian scenario, we allow the SR procedure to be “out of tune” in the way of the post-change distribution parameter, and numerically assess the effect of the “mistuning” on Shiryaev's (multi-cyclic) Stationary Average Detection Delay delivered by the SR procedure. The comprehensive quantitative robustness characterization of the SR procedure obtained in the study can be used to develop the respective theory as well as to provide a rational for practical design of the SR procedure. The overall qualitative conclusion of the study is an expected one: the SR procedure is less (more) robust for less (more) contrast changes and for lower (higher) levels of the false alarm risk.     

Retrospective change detection in categorical time series

The aim of this paper is to propose methods of detecting change in the coefficients of a multinomial logistic regression model for categorical time series offline. The alternatives to the null hypothesis of stationarity can be either the hypothesis that it is not true, or that there is a temporary change in the sequence. We use the efficient score vector of the partial likelihood function. This has several advantages. First, the alternative value of the parameter does not have to be estimated; hence, we have a procedure that has a simple structure with only one parameter estimation using all available observations. This is in contrast with the generalized likelihood ratio-based change point tests. The efficient score vector is used in various ways. As a vector, its components correspond to the different components of the multinomial logistic regression model’s parameter vector. Using its quadratic form a test can be defined, where the presence of a change in any or all parameters is tested for. If there are too many parameters one can test for any subset while treating the rest as nuisance parameters. Our motivating example is a DNA sequence of four categories, and our test result shows that in the published data the distribution of the four categories is not stationary.     

论无效婚姻过错赔偿制度

20 0 1年婚姻法建立了比较完整的无效婚姻制度 ,这是婚姻家庭法领域的一项重大的进步。但我国目前的无效婚姻制度仍有不足之处 ,本文所述的无效婚姻过错赔偿责任就是其一。本文主要分析设立无效婚姻赔偿责任的必然性和可能性、构成无效婚姻过错赔偿责任的条件、损害赔偿的范围、无效婚姻过错赔偿责任与财产分割的关系和赔偿请求权的行使     

论杀人犯罪被害人与刑事司法参与

杀人犯罪被害人是指因杀人犯罪行为而遭受直接侵害的自然人。杀人犯罪被害人参与刑事司法,具有重要意义和价值,其途径主要有量刑参与和刑事和解。此外,在被害人具有过错的情况下,其也以独特的方式参与到刑事司法程序之中。     

冯契的逻辑范畴学说及其方法论意义

作为当代著名的哲学家、逻辑学家,冯契对逻辑范畴作了开拓性的探索：阐明了逻辑范畴的辩证本性和特点;考察了逻辑范畴体系与认识的辩证运动;建构了以“类”、“故”、“理”为骨架的逻辑范畴体系;探讨了以“类”、“故”、“理”为骨架的逻辑范畴体系的方法论意义。     

遗传算法在入侵检测中的应用

介绍了基于模型推理和基于模型两种入侵检测系统,提出了一种新的基于智能体技术的入侵检测系统体系结构,解决了传统集中式入侵检测系统的弊病,将任务处理和数据分布到网络各个结点上,充分利用网络资源协同完成入侵检测任务;介绍了遗传算法在该系统中的应用,因系统安全的先验知识体现在对原始数据中有价值特征属性变量集的选择上,故利用遗传算法对特征属性变量子集的选择进行优化,找到相对最优的由特征向量表示的特征属性变量集,以降低入侵检测系统的负荷。