转子支承参数识别的试验验证

本文用半试验半数值分析的方法识别转子的支承参数。在实验室条件下,对实际转子进行了试验、测量、计算和识别。所得结果令人满意,其精度可以满足工程上的要求。     

中美玉米期货市场风险溢出效应研究

为研究中美玉米期货市场风险溢出效应的方向和大小,选取2006年1月4日至2017年5月31日大连商品期货交易所和芝加哥商品交易所中的玉米主力连续价格以及央行外汇中间价的日数据为样本数据,并将样本期间分为3个阶段,借助平稳性检验、相关性检验,采用EGARCH-GED模型、VaR模型和格兰杰因果检验来研究两市玉米期货的风险溢出效应。研究发现,中美两国玉米期货市场的风险存在正相关性,且在金融危机期间风险相关性明显增强并存在双向的风险溢出效应;在金融危机之前,美国玉米期货市场对中国玉米期货市场有风险溢出效应。     

通过保障对质询问权实现庭审实质化——欧美对质询问权判例的考察及启示

坚持以审判为中心的诉讼制度改革是中国当前刑事司法改革的方向,庭审实质化是坚持以审判为中心的诉讼制度改革的必要组成部分。《刑事诉讼法》对关键证人出庭作证制度做出了相应的规定,但是对被告人对质询问权保障的规定还需要进一步的细化。《欧洲人权公约》第6条第3款（d）项和美国宪法第6修正案都规定了对被告人对质询问权的保障,并且在这两个地区都产生了具有指导意义的判例。欧洲人权法院对质询问权的保障经历了从“唯一、决定性规则”向“三步检验规则”的转变,美国对质询问权的保障也经历了从“可靠性标准”向“证言性陈述标准”的转变,对被告人的对质询问权起到了重要的保障作用。中国对质询问权的保障应当在现有关键证人作证制度的基础上进行细化规定,坚持证人出庭作证为原则、不出庭作证为例外,并明确规定例外情形和救济措施,从时间和空间上实现对对质询问权的保障。     

陷入“惩戒牢笼”:失信惩戒是否抑制了企业创新?——来自废水国控重点监测企业的证据

失信惩戒对企业污染违规治理已初见成效,然而对企业技术创新的影响却鲜有关注。以京津冀、长三角、珠三角地区的废水国控重点监测企业为研究对象,基于制度基础观理论提出失信惩戒对企业技术创新的"惩戒牢笼"假说,并通过使用地区腐败作为工具变量的截面数据模型的两阶段最小二乘（2SLS）回归发现:（1）失信惩戒与企业创新之间具有显著的负向因果关系,受"惩戒牢笼"所捕获的企业其研发创新活动受到了显著的抑制,惩戒强度越强,企业的技术创新产出越低;（2）国有企业正向调节失信惩戒与企业创新的负向因果关系,且主效应为正,这在于国有企业的"合法性"基因使其具有更强的惩戒免疫力,高压惩戒反而提升了其创新意愿,其研发创新与惩戒强度正相关。稳健性检验证实了研究结论的可靠性。     

Outlier detection in contingency tables using decomposable graphical models

For high-dimensional data, it is a tedious task to determine anomalies such as outliers. We present a novel outlier detection method for high-dimensional contingency tables. We use the class of decomposable graphical models to model the relationship among the variables of interest, which can be depicted by an undirected graph called the interaction graph. Given an interaction graph, we derive a closed-form expression of the likelihood ratio test (LRT) statistic and an exact distribution for efficient simulation of the test statistic. An observation is declared an outlier if it deviates significantly from the approximated distribution of the test statistic under the null hypothesis. We demonstrate the use of the LRT outlier detection framework on genetic data modeled by Chow–Liu trees.     

Extending the Barnard’s test to non-inferiority

In 1945, George Alfred Barnard presented an unconditional exact test to compare two independent proportions. Critical regions for this test, by construction accomplish the very useful property of being Barnard convex sets. Besides, there are empirical findings suggesting that Barnard’s test is the most generally powerful. For Barnard’s test, calculation of critical regions is complicated due that they are constructed in an iterative form until is obtained a test size, as close as possible to the nominal significance level and less than or equal to it. In this article we present an extension to non-inferiority of this very leading test. This extension was contructed for any dissimilarity measure and tables were constructed for the difference between proportions. Also we calculate the critical regions for this extended test for sample sizes less or equal than 30, nominal significance level 0.01, 0.025, 0.05, and 0.10 and for non-inferiority margins 0.05, 0.10, 0.15, and 0.20. Additionally, we computed test sizes for the mentioned configurations. To do this calculations, we have written a program in the R environment.     

An evaluation of change-point estimators for a sequence of normal observations with unknown parameters

Performance of maximum likelihood estimators (MLE) of the change-point in normal series is evaluated considering three scenarios where process parameters are assumed to be unknown. Different shifts, sample sizes, and locations of a change-point were tested. A comparison is made with estimators based on cumulative sums and Bartlett's test. Performance analysis done with extensive simulations for normally distributed series showed that the MLEs perform better (or equal) in almost every scenario, with smaller bias and standard error. In addition, robustness of MLE to non-normality is also studied.     

Non-parametric MANOVA approaches for non-normal multivariate outcomes with missing values

Between-group comparisons often entail many correlated response variables. The multivariate linear model, with its assumption of multivariate normality, is the accepted standard tool for these tests. When this assumption is violated, the non-parametric multivariate Kruskal–Wallis (MKW) test is frequently used. However, this test requires complete cases with no missing values in response variables. Deletion of cases with missing values likely leads to inefficient statistical inference. Here we extend the MKW test to retain information from partially observed cases. Results of simulated studies and analysis of real data show that the proposed method provides adequate coverage and superior power to complete case analyses.     

Preenrollment Immunization Policies of American Colleges: An Assessment of the Need for Policy Implementation

Abstract

Alcohol abuse among college students is prevalent, yet few instruments with sound reliability and validity are available to assess these problems in this population. As part of a large, baseline assessment battery for a prospective study of offspring of alcoholics, the 27-item Young Adult Alcohol Problems Screening Test (YAAPST) was given to 490 freshmen at a large mid western university; approximately 9 months later, 482 subjects completed the scale again. In addition to asking about such traditional problems as experiencing blackouts and driving while intoxicated, the YAAPST included specific items relating to college experiences (eg, getting into sexual situations that were later regretted, missing classes, and receiving lower grades than usual). The YAAPST was designed to assess these drinking consequences over two different time frames, lifetime and past year, and also to indicate the frequency of occurrence during the past year. Results indicated that the YAAPST is a unidimensional scale with good psychometric properties (good internal consistency and test-retest reliability). Three different approaches were used to demonstrate the validity of the YAAPST. Findings supported criterion validity (with interview-based alcohol abuse/dependence diagnoses as the criterion), concurrent validity (comparing the YAAPST with other drinking measures), and construct validity (correlating the YAAPST with etiologically relevant personality, motivational, and peer influence variables). The YAAPST is a promising screening instrument for alcohol problems in college students. It has excellent psychometric properties and the potential to provide a range of useful information to the clinician or researcher.     

Testing for a separation between two normal distributions

Three tests are proposed for testing for a specified degree of overlap between two normal distributions, The hypotheses considered are an extension of the Behrens-Fisher problem, A simulation study of the performance of the tests is presented.