大锻件统计学Chi-square test的研究和应用

根据大锻件生产的特点和统计学的基本理论方法,首次深入浅出地论述了大锻件的Chi-square test,即X2检验,并给出了具体应用示例。该方法可用于大锻件工艺参数的科学分析和生产验证,可用于大锻件质量分析和判断,可帮助逐步建立起大锻件的工序能力,帮助实现稳定并提升大锻件工艺和质量控制水平。

Large Deviations and Moderate Deviations for the Chi-Square Test in Type Ⅱ Error

We study the asymptotics tot the statistic of chi-square in type Ⅱ error. By the contraction principle, the large deviations and moderate deviations are obtained, and the rate function of moderate deviations can be calculated explicitly which is a squared function.

Use of Pearson’s Chi-Square for Testing Equality of Percentile Profiles across Multiple Populations

In large sample studies where distributions may be skewed and not readily transformed to symmetry, it may be of greater interest to compare different distributions in terms of percentiles rather than means. For example, it may be more informative to compare two or more populations with respect to their within population distributions by testing the hypothesis that their corresponding respective 10th, 50th, and 90th percentiles are equal. As a generalization of the median test, the proposed test statistic is asymptotically distributed as Chi-square with degrees of freedom dependent upon the number of percentiles tested and constraints of the null hypothesis. Results from simulation studies are used to validate the nominal 0.05 significance level under the null hypothesis, and asymptotic power properties that are suitable for testing equality of percentile profiles against selected profile discrepancies for a variety of underlying distributions. A pragmatic example is provided to illustrate the comparison of the percentile profiles for four body mass index distributions.

A Simple Chi-Square Statistic for Testing Homogeneity of Zero-Inflated Distributions

Zero-inflated distributions are common in statistical problems where there is interest in testing homogeneity of two or more independent groups. Often, the underlying distribution that has an inflated number of zero-valued observations is asymmetric, and its functional form may not be known or easily characterized. In this case, comparisons of the groups in terms of their respective percentiles may be appropriate as these estimates are nonparametric and more robust to outliers and other irregularities. The median test is often used to compare distributions with similar but asymmetric shapes but may be uninformative when there are excess zeros or dissimilar shapes. For zero-inflated distributions, it is useful to compare the distributions with respect to their proportion of zeros, coupled with the comparison of percentile profiles for the observed non-zero values. A simple chi-square test for simultaneous testing of these two components is proposed, applicable to both continuous and discrete data. Results of simulation studies are reported to summarize empirical power under several scenarios. We give recommendations for the minimum sample size which is necessary to achieve suitable test performance in specific examples.

基于Chi-square检验的分布式网络入侵检测系统

针对网络攻击的新特点,本文提出了一种基于Chi-square检验的分布式网络入侵检测系统模型CTDIDS。设计并实现了一个基于异常检测的入侵分析引擎。通过对网络数据包的分析,运用Chi-square值比较对系统的行为进行检测。与现有的入侵检测方法相比,本文提出的方法具有更好的环境适应性和数据协同分析能力。实验证明,分布式入侵检测系统CTDIDS具有更高的准确性和扩展性。

Chi-Square Distribution: New Derivations and Environmental Application

We describe two new derivations of the chi-square distribution. The first derivation uses the induction method, which requires only a single integral to calculate. The second derivation uses the Laplace transform and requires minimum assumptions. The new derivations are compared with the established derivations, such as by convolution, moment generating function, and Bayesian inference. The chi-square testing has seen many applications to physics and other fields. We describe a unique version of the chi-square test where both the variance and location are tested, which is then applied to environmental data. The chi-square test is used to make a judgment whether a laboratory method is capable of detection of gross alpha and beta radioactivity in drinking water for regulatory monitoring to protect health of population. A case of a failure of the chi-square test and its amelioration are described. The chi-square test is compared to and supplemented by the t-test.

HFACS-MI改进模型在危险化学品仓储事故人因分析中的应用

为了研究危险化学品仓储事故的关键人因,通过人因分析与分类系统-煤矿(Human Factors Analysis and Classification System-Mine,HFACS-MI)改进模型从员工的不安全行为、影响不安全行为的前提条件、监督行为、组织影响和企业外部因素5个层次系统地分析65起危险化学品仓储事故,并运用卡方检验和让步比分析了产生不安全行为的原因和各层次间的内在关系。结果表明,外部管理、组织过程、监督不充分、个人因素、技能差错和违规是导致危险化学品仓储事故发生的重要因素。HFACS-MI改进模型上下层级的人为因素间存在显著的因果关系,且主要的危险化学品仓储事故致因路径共有5条,其中“外部管理因素—组织过程漏洞—监督不充分—个人因素—违规”是最关键的致因路径。改进的HFACS-MI模型可以有效分析危险化学品仓储事故人因因素。

基于Chi-quare检验与词义分析的试题重复检测算法

针对无纸化考试系统入库试题重复检测问题;提出基于卡方检验与词义分析的试题重复检测算法,首先自动提取试题的特征信息词项,利用卡方检验改进公式进行特征词分析并删除冗余词;其次,结合中文WordNet词典对特征词进行词义分析,并利用Tf-Idf方法计算入库试题的特征词向量与不同题型特征词的余弦相似度;最后,根据所得相似度值判别该试题是否与题库试题重复。实验结果表明,在重复度阀值选取0.8时,算法耗时少、准确性高。

基于K-Means聚类与灰色关联分析对玻璃文物成分的研究

古代玻璃制品极易受埋藏环境的影响而风化,导致玻璃文物成分比例发生变化,从而影响对其类别的正确判断。文章针对古代玻璃制品的成分分析与鉴别问题,使用卡方检验、K-Means均值聚类、分层聚类、灰色关联等方法,构建卡方模型、BP神经网络模型、K-Means均值聚类模型、灰色关联分析等,运用Matlab、SPSS、Python等软件编程,研究了玻璃类型高钾与铅钡的分类依据,并对不同类别玻璃按照化学成分进行亚分类,分析了其化学成分的统计规律与关联关系。最后利用单因素方差分析法,检验了模型的合理性。

基于BIG-WFCHI的微博信息关键特征选择方法

特征选择是用机器学习方法提高转发预测精度和效率的关键步骤,其前提是特征提取.目前,特征选择中常用的方法有信息增益(Information Gain,IG)、互信息和卡方检验(CHI-square test,CHI)等,传统特征选择方法中出现低频词引起的信息增益和卡方检验的负相关、干扰计算等问题,导致分类准确率不高.本文首先针对低频词引起的信息增益和卡方检验的负相关、干扰计算等问题进行研究,分别引入平衡因子和词频因子来提高算法的准确率;其次,根据微博信息传播的特点,结合改进的IG算法和CHI算法,提出了一种基于BIG-WFCHI(Balance Information Gain-Word Frequency CHI-square test)的特征选择方法.实验分析中,本文采用基于最大熵模型、支持向量机、朴素贝叶斯分类器、KNN和多层感知器5种分类器对两个异构数据集进行了测试.实验结果表明,本文提出的方法能有效消除无关特征和冗余特征,提高分类精度,并减少运算时间.

A Note on Cochran Test for Homogeneity in Two Ways ANOVA and Meta-Analysis

In this paper, we generalize the proof of the Cochran statistic in the case of an ANOVA two ways structure that asymptotically follows a Chi-2. While construction of homogeneity statistics test usually resorts to the determination of the covariance matrix and its inverse, the Moore-Penrose matrix, our approach, avoids this step. We also show that the Cochran statistic in ANOVA two ways is equivalent to conventional homogeneity statistics test. In particular, we show that it satisfies the invariance property. Finally, we conduct empirical verification from a meta-analysis that confirms our theoretical results.

GNSS/SINS/视觉导航鲁棒算法

全球导航卫星系统(Global Navigation Satellite System, GNSS)、捷联惯性导航系统(Strapdown Inertial Navigation System, SINS)和视觉传感器优势互补,3者信息融合可获得高精度、无漂移的导航定位信息.针对GNSS/SINS/视觉融合导航易受运动速度、光照变化、遮挡等影响导致定位精度和鲁棒性降低问题,本文在图优化框架的代价函数中加入SoftLOne鲁棒核函数,设置量测值粗差检验程序,降低离群点带来的负面影响.进一步,对量测值计算残差进行卡方检验,对超限残差降权处理,提高系统精度和鲁棒性.实验结果表明,本文算法较不施加鲁棒核函数、不采用异常值剔除策略和卡方检验的传统算法,以及加入其他鲁棒核函数的算法精度更高、鲁棒性更好,能够较大程度提升GNSS/SINS/视觉导航定位精度和鲁棒性,在大尺度环境下,未出现较大漂移误差,绝对位姿均方根误差0.735 m,绝对位姿误差标准差0.336 m.

高校实验室安全事故人为因素及其影响路径分析

为了通过人因分析与分类系统模型从组织影响、不安全的监督、不安全行为的前提条件和不安全行为4个层面探究高校实验室安全事故的关键人因及其影响路径。对90起高校实验室事故(2000—2022年)进行统计分析,并运用卡方检验和让步比探讨了产生不安全行为的原因和各层次间的内在联系。结果表明:组织过程简单、监督不充分、个人因素、技能失误和习惯性违规是导致高校实验室事故发生的重要因素;模型中高低层级的人为因素间存在显著的因果关系,且主要的实验室事故致因路径共有16条。根据各层级事故致因形式,剖析了针对性的高校实验室事故的影响过程。

组织视角下的核电厂班组决策失误致因分析

为了系统研究班组决策失误规律,识别核电厂班组决策失误的关键路径,从组织视角出发,结合核电厂所处环境与班组决策失误特征对人因分析与分类系统(Human Factor Analysis and Classification System,HFACS)模型进行改进,建立了核电厂班组决策失误致因模型。利用改进后的模型对137份核电厂事件报告进行统计分析,并运用卡方检验与让步比分析班组决策失误的原因及各层次之间的内在关系。结果表明,组织文化缺失、规程不明晰、知识与能力不足、制定备选方案失误是导致班组决策失误的重要因素。改进HFACS模型中上下层级的因素之间存在显著的因果关系,且容易引发班组决策失误的路径有32条,其中发生概率最大的路径为组织设计不当→任务不明晰→压力过大→确定目标失误。由此可见,核电事故的发生是各致因因素相互作用的结果,降低班组决策失误概率需要阻断关键致因路径,加强对关键因素的管控。

基于HFACS的道路运输事故致因分析与分类系统研究

为了深入研究道路运输事故的致因因素,挖掘出关键致因规则,在人因分析和分类系统(HFACS)的基础上,构建道路运输事故致因分析与分类系统(RTAACS),并根据该系统框架对收集到的事故进行分析。首先将RTAACS框架分为监管部门、道路运输企业、驾驶人3个层级,将事故致因因素纳入该系统框架进行频率统计,通过R语言改进卡方检验、让步比分析得出致因因素之间的关联规则,最后根据ANP网络层次分析法计算各项致因因素的权重,并确定关键致因规则。结果表明:工作流程与不充分的企业监督、工具技术与习惯性违规、资源管理与工具技术、资源管理与习惯性违规、未纠正的已知错误与习惯性违规为道路运输事故的关键致因规则。研究构建的系统框架以及提出的分析方法为道路运输业的安全预防提供一定的借鉴意义。

A Modified Chi-Squared Goodness-of-Fit Test

In goodness-of-fit tests,Pearson's chi-squared test is one of most widely used tools of formal statistical analysis.However,Pearson's chi-squared test depends on the partition of the sample space.Different constructions of the partition of the sample space may lead to different conclusions.Based on an equiprobable partition of sample space,a modified chi-squared test is proposed.A method for constructing the modified chi-squared test is proposed.As an application,the proposed test is used to test whether vectorial data come from an uniformity distribution defined on the hypersphere.Some simulation studies show that the modified chi-squared test against different alternative is robust.

Consistency of Chi-Squared Test with Varying Number of Classes

The classical chi-squared goodness of fit test assumes the number of classes is fixed,meanwhile the test statistic has a limiting chi-square distribution under the null hypothesis.It is well known that the number of classes varying with sample size in the test has attached more and more attention.However,in this situation,there is not theoretical results for the asymptotic property of such chi-squared test statistic.This paper proves the consistency of chi-squared test with varying number of classes under some conditions.Meanwhile,the authors also give a convergence rate of KolmogorovSimirnov distance between the test statistic and corresponding chi-square distributed random variable.In addition,a real example and simulation results validate the reasonability of theoretical result and the superiority of chi-squared test with varying number of classes.

融合反讽语言特征的反讽语句识别模型

反讽是采用内隐的形式来表达情感的一种方法,反讽语句在文字和所想表达的情感上存在着不同,这使得对反讽语句进行情感分类变得更加困难。针对这一现象,提出一种融合反讽语言特征的反讽语句识别模型,通过加入反讽语言特征来提高反讽语句的识别准确率。首先,采用卡方检验算法对反讽语言进行分析并获取语言特征;然后,利用Word2Vec对语言特征进行训练获取语言特征的特征表示,同时使用注意力机制与Bi-GRU(双向门控循环神经单元)模型获取句子的特征表示;最后,将语言特征的特征表示与句子的特征表示进行融合并作为情感分类层的输入,对反讽语句进行识别。与CNN-AT、CNN-Adv、EPSN等3种模型进行对比,实验结果表明,该模型可以有效提高对于反讽语句的识别准确率。

基于统计分析方法对古代玻璃制品的成分探究

利用斯皮尔曼相关系数和卡方检验分析了古代玻璃的成分,得出玻璃类型、纹饰、颜色与表面风化的相关性和差异性;对风化玻璃制品数据借助中位数、平均值、标准差等指标进行对比分析,通过加权平均值预测模型,预测风化前玻璃状态,得出玻璃类型的鉴别方法。利用敏感度系数公式,得到二氧化硅含量增减10%与氧化铅含量比值,说明氧化铅和二氧化硅含量的微量改变不会对类别产生影响。借助相关性分析和数据透视表得出高钾玻璃和铅钡玻璃二氧化硅含量较多,风化前氧化铝、氧化钙、氧化铜含量均较高,钾玻璃风化后化学成分关联性较弱,铅钡玻璃风化后化学成分关联性较强。