一种基于加权F-范数的半正定矩阵的逼近方法

正定性是许多金融预测模型的重要假设前提，然而从实际样本中得到的相关系数矩阵并不能保证其正定性。为此在介绍如何根据样本设定相关系数矩阵以及范数逼近原理的基础上，如何根据该原理找到与之最接近的相关系数矩阵，即最接近的单位对角半正定对称矩阵。通过实证，验证了其方法的有效性。     

玻利维亚锡矿工的阶级意识——读《我们吃矿,矿吃我们》

<正>《我们吃矿,矿吃我们》②是美国女性人类学家纳什(June Nash)关于玻利维亚锡矿工人的经典民族志作品。纳什于1969年到玻利维亚锡矿山做田野,当时她42岁,还带着一个女儿,整个1970年她都在田野中。调查的敏感性使得她被矿工和CIA同时监视,但她最终获得了矿工的接纳。1971年她着手整理矿工Juan Rojas的口述历史,于1976年以西班牙文发表。《我们吃矿,矿吃我们》初版于1979年,1993年该书再版时,     

几种传输线的场分布

求开放平板线、外正三角形內圆同轴线、外方內圆同轴线、外正六边形內圆同轴线的特性阻抗而建立的精确保角变换的基础上,本文进一步讨论了显式逆变换函数,从而求得了这几种传输线的场分布的闭合表达式。由于所用保角变换的精确性,所得的显式场分布在内导体和外导体的内接圆尺寸之比小于0.5in。基本上是准确的,在这个尺寸比稍大些时也可作为参考。这些场分布对于了解传输线的功率容量,计算衰减常数,考虑功率耦合,设计有关的有源器件等都是必不可少的。文中获得的几种传输线的场分布的显著特点是计算方便,在一般实用范围內有足够的精度。     

A Note on Inconsistency of NPMLE of the Distribution Function from Left Truncated and Case I Interval Censored Data

We show that under reasonable conditions the nonparametric maximum likelihood estimate (NPMLE) of the distribution function from left-truncated and case 1 interval-censored data is inconsistent, in contrast to the consistency properties of the NPMLE from only left-truncated data or only interval-censored data. However, the conditional NPMLE is shown to be consistent. Numerical examples are provided to illustrate their finite sample properties.     

关于平面对称紧凸集不等式

本文简论平面对称紧凸集不等式问题,引伸Favard不等式,对不等式中的相关常数给出两种证法。     

从制度和文化层面看现代企业集团的经济性

现代企业集团是世界经济发展过程中的一个普遍现象,它对于推动社会生产力的发展具有重要意义。本文首先从企业集团的特征入手,分析了现代企业集团的实质;其次,从制度和文化两个层面,分析了现代企业集团的组织经济性和名牌经济性     

光谱法测量等离子体离子温度和再循环粒子流速

利用多道光学分析仪（OSMA）测量HT-6M托卡马克限制器前Hα线形分布,通过高斯拟合由多普勒展宽和多普勒频移分别得出等离子体离子温度和再循环粒子流速。     

A Multiple Imputation Approach to Linear Regression with Clustered Censored Data

Weextend Wei and Tanner's (1991) multiple imputation approach insemi-parametric linear regression for univariate censored datato clustered censored data. The main idea is to iterate the followingtwo steps: 1) using the data augmentation to impute for censoredfailure times; 2) fitting a linear model with imputed completedata, which takes into consideration of clustering among failuretimes. In particular, we propose using the generalized estimatingequations (GEE) or a linear mixed-effects model to implementthe second step. Through simulation studies our proposal comparesfavorably to the independence approach (Lee et al., 1993), whichignores the within-cluster correlation in estimating the regressioncoefficient. Our proposal is easy to implement by using existingsoftwares.     

Segmentation,alignment and statistical analysis of biosignals with application to disease classification

We present a novel methodology for a comprehensive statistical analysis of approximately periodic biosignal data. There are two main challenges in such analysis: (1) the automatic extraction (segmentation) of cycles from long, cyclostationary biosignals and (2) the subsequent statistical analysis, which in many cases involves the separation of temporal and amplitude variabilities. The proposed framework provides a principled approach for statistical analysis of such signals, which in turn allows for an efficient cycle segmentation algorithm. This is achieved using a convenient representation of functions called the square-root velocity function (SRVF). The segmented cycles, represented by SRVFs, are temporally aligned using the notion of the Karcher mean, which in turn allows for more efficient statistical summaries of signals. We show the strengths of this method through various disease classification experiments. In the case of myocardial infarction detection and localization, we show that our method compares favorably to methods described in the current literature.     

A note on statistical method for genotype calling of high-throughput single-nucleotide polymorphism arrays

We study the genotype calling algorithms for the high-throughput single-nucleotide polymorphism (SNP) arrays. Building upon the novel SNP-robust multi-chip average preprocessing approach and the state-of-the-art corrected robust linear model with Mahalanobis distance (CRLMM) approach for genotype calling, we propose a simple modification to better model and combine the information across multiple SNPs with empirical Bayes modeling, which could often significantly improve the genotype calling of CRLMM. Through applications to the HapMap Trio data set and a non-HapMap test set of high quality SNP chips, we illustrate the competitive performance of the proposed method.