基于时频分析的裂纹转子碰摩故障特征研究

为研究转子系统耦合故障特性,采用有限元方法建立了含有横向裂纹、转静碰摩的非线性转子动力学模型。首先研究了不同转速下裂纹、碰摩单一故障下转子系统的振动响应,其次研究了两种故障耦合情况下系统的振动响应特征。采用波形图、FFT谱图、瞬时频率和Hilbert-Huang时频谱(HHS)相结合的方法对故障转子振动信号进行了分析。分析结果表明:运用多种时频分析相结合的方法可以较为全面地了解转子的故障特征,裂纹转子在1/5、1/3临界转速时会发生较为明显的5X、3X谐波,且裂纹的产生会导致响应幅值增大,从而引起更为严重的碰摩。      

Semiparametric Bayesian classification with longitudinal markers

Summary.  We analyse data from a study involving 173 pregnant women. The data are observed values of the β human chorionic gonadotropin hormone measured during the first 80 days of gestational age, including from one up to six longitudinal responses for each woman. The main objective in this study is to predict normal versus abnormal pregnancy outcomes from data that are available at the early stages of pregnancy. We achieve the desired classification with a semiparametric hierarchical model. Specifically, we consider a Dirichlet process mixture prior for the distribution of the random effects in each group. The unknown random-effects distributions are allowed to vary across groups but are made dependent by using a design vector to select different features of a single underlying random probability measure. The resulting model is an extension of the dependent Dirichlet process model, with an additional probability model for group classification. The model is shown to perform better than an alternative model which is based on independent Dirichlet processes for the groups. Relevant posterior distributions are summarized by using Markov chain Monte Carlo methods.     

Bayesian analysis of human movement curves

Summary.  We consider the Bayesian analysis of human movement data, where the subjects perform various reaching tasks. A set of markers is placed on each subject and a system of cameras records the three-dimensional Cartesian co-ordinates of the markers during the reaching movement. It is of interest to describe the mean and variability of the curves that are traced by the markers during one reaching movement, and to identify any differences due to covariates. We propose a methodology based on a hierarchical Bayesian model for the curves. An important part of the method is to obtain identifiable features of the movement so that different curves can be compared after temporal warping. We consider four landmarks and a set of equally spaced pseudolandmarks are located in between. We demonstrate that the algorithm works well in locating the landmarks, and shape analysis techniques are used to describe the posterior distribution of the mean curve. A feature of this type of data is that some parts of the movement data may be missing—the Bayesian methodology is easily adapted to cope with this situation.     

Comparison of different estimation techniques for portfolio selection

The main problem in applying the mean-variance portfolio selection consists of the fact that the first two moments of the asset returns are unknown. In practice the optimal portfolio weights have to be estimated. This is usually done by replacing the moments by the classical unbiased sample estimators. We provide a comparison of the exact and the asymptotic distributions of the estimated portfolio weights as well as a sensitivity analysis to shifts in the moments of the asset returns. Furthermore we consider several types of shrinkage estimators for the moments. The corresponding estimators of the portfolio weights are compared with each other and with the portfolio weights based on the sample estimators of the moments. We show how the uncertainty about the portfolio weights can be introduced into the performance measurement of trading strategies. The methodology explains the bad out-of-sample performance of the classical Markowitz procedures.     

Multiple-arm superiority and non-inferiority designs with various endpoints

Multiple-arm dose-response superiority trials are widely studied for continuous and binary endpoints, while non-inferiority designs have been studied recently in two-arm trials. In this paper, a unified asymptotic formulation of a sample size calculation for k-arm (k>0) trials with different endpoints (continuous, binary and survival endpoints) is derived for both superiority and non-inferiority designs. The proposed method covers the sample size calculation for single-arm and k-arm (k> or =2) designs with survival endpoints, which has not been covered in the statistic literature. A simple, closed form for power and sample size calculations is derived from a contrast test. Application examples are provided. The effect of the contrasts on the power is discussed, and a SAS program for sample size calculation is provided and ready to use.     

基于RS分析的中国债券市场分形特征研究

文章详细讨论了RS分析方法、概率空间分形维的测度,通过对上证国债指数和上证企债指数的RS分析,得到了两序列赫斯特指数和非周期循环长度,进一步得出中国债券市场为分形市场的结论.     

中国产业结构变动与就业水平的实证研究

文章运用时间序列和计量模型研究了中国产业结构与就业水平之间的发展关系.首先运用格兰杰因果检验分析了第一、二、三次产业的产值与其就业之间的因果影响关系,继而从产值与就业两个角度定量分析了第一、二、三次产业各自对总就业水平的贡献,得出结论:第一产业和第三产业是劳动力就业的决定因素,而第二产业不是就业的决定因素;从产值角度来看,第三产业对劳动力就业的贡献最大,从就业角度来看,第一产业的就业对总体就业水平的贡献最高,其次是第三产业,而第二产业的就业对总体就业水平的贡献最小.最后根据研究结论提出相应的建议措施.     

中国基础设施投资对经济增长波动的冲击效应分析

基础设施是经济发展的重要影响因素，而“基础设施投资促进经济发展”这一主流观点已得到广泛共识，但人们对经济增长与基础设施的探讨仅局限于总量的分析框架，并未对基础设施的类型加以区分，更没发现经济发展的不同阶段对基础设施的需求结构也是不同的。而以“基础设施投资促进经济发展”为出发点，将基础设施投资细分为生产性、生活性、社会性基础设施投资，并分别讨论其对经济的影响。通过邹检验发现：自1994年以来，基础设施投资冲击改变了中国经济增长的特征。其结论是生产性、生活性基础设施对经济增长的影响是明确的、同步的，但社会性基础设施对经济增长的作用是不确定的。因此，加强社会性基础设施投资是一个渐进地逐步推进的过程。     

大学生数学成绩影响因素的实证分析

伴随着近几年高校的扩大招生,部分大学生的数学成绩显著下降。用统计学软件SPSS 13.0对哈尔滨工程大学部分学生的高等数学成绩及其相关因素进行统计分析,考察学生的高考数学成绩、性别、生源所在地等因素对其大学数学成绩的影响。在给出了一些切实可行的对策和建议的同时,指出培养大学生学习的主动性和研究探索精神,已经成为当今高校教师和教育工作者培养高素质人才和提高教学水平的关键。     

我国商业银行无形资产统计问题研究

摘　　要:商业银行无形资产是形成商业银行核心竞争力的基础和产生超额收益的源泉,加强商业银行无形资产统计工作,有利于充分揭示商业银行无形资产基本内容和对核心竞争力的影响。笔者认为,目前我国商业银行无形资产统计指标体系设置不完整,统计制度不健全,统计内容不全面,统计分析不深入,影响经济决策。笔者认为,完善商业银行无形资产统计制度时,应从组织结构类、客户关系类、知识创新类和人力资本类等四个方面对无形资产进行统计,逐步细化统计指标,明确具体的统计内容,建立、健全无形资产价值信息系统,深化无形资产统计分析工作,以此为基础,提出提高商业银行核心竞争力的基本策略。