Random sliced inverse regression

Sliced Inverse Regression (SIR; 1991) is a dimension reduction method for reducing the dimension of the predictors without losing regression information. The implementation of SIR requires inverting the covariance matrix of the predictors—which has hindered its use to analyze high-dimensional data where the number of predictors exceed the sample size. We propose random sliced inverse regression (rSIR) by applying SIR to many bootstrap samples, each using a subset of randomly selected candidate predictors. The final rSIR estimate is obtained by aggregating these estimates. A simple variable selection procedure is also proposed using these bootstrap estimates. The performance of the proposed estimates is studied via extensive simulation. Application to a dataset concerning myocardial perfusion diagnosis from cardiac Single Proton Emission Computed Tomography (SPECT) images is presented.     

The Donation Paradox for Peremptory Challenges

A donation paradox occurs when a player gives an apparently valuable prerogative to another player, but does better, according to some criterion. Peremptory challenges, used in choosing a American jury, permit each side to veto a certain number of potential jurors. With even a very simple model of jury selection, it is shown that for one side to give a peremptory challenge to the other side may lead to a more favorable jury, an instance of the donation paradox. Both a theorem and examples are given concerning the existence of the donation paradox in the optimal use of peremptory challenges.     

Dimension reduction for the conditional mean and variance functions in time series

This paper deals with the nonparametric estimation of the mean and variance functions of univariate time series data. We propose a nonparametric dimension reduction technique for both mean and variance functions of time series. This method does not require any model specification and instead we seek directions in both the mean and variance functions such that the conditional distribution of the current observation given the vector of past observations is the same as that of the current observation given a few linear combinations of the past observations without loss of inferential information. The directions of the mean and variance functions are estimated by maximizing the Kullback–Leibler distance function. The consistency of the proposed estimators is established. A computational procedure is introduced to detect lags of the conditional mean and variance functions in practice. Numerical examples and simulation studies are performed to illustrate and evaluate the performance of the proposed estimators.     

Blog offensive: An exploratory analysis of attacks published on campaign blog posts from a political public relations perspective

An advancement in online campaigning during the 2004 election cycle was the integration of blogs in candidate Web sites. This content analysis investigated the political public relations message strategy on campaign blogs during the 2004 election, focusing on attacks as a part of Functional Theory of Political Campaign Discourse. Results indicated frequent discussion of the opponent, reliance on attacks, and the dominance of logical appeals. Candidates focused on issue over image. The incumbent attacked more often than the challenger.     

关于线性变换的根子空间

本文系统论述了属于线性变换特征概念范围的根子空间的基本问题，主要的有两点：（１）根向量所属于的特征值的唯一性；（２）根子空间与特征子空间的结构关系，作为论述这两个问题的预备定理，文中还证明了根向量或根子空间的其它两个重要性质。     

麦克风阵列二维方向估计聚焦算法研究

聚焦算法是解决宽带信号方向(DOA)估计问题的重要算法。常规的宽带聚焦算法需要进行预估计和多次迭代,算法的计算复杂度较高。该文根据宽带聚焦算法的思想,结合语音信号的特点,以各频率点的频域相关矩阵和聚焦点的相关矩阵的均方误差最小为最优化准则,提出了一种不需要预估计和迭代的二维宽带聚焦算法。该算法实时性好、计算复杂度低。采用八元均匀圆环麦克风阵列,仿真验证了该算法的良好二维DOA估计性能。     

一致有界实值函数集上的最佳同时逼近

给出了最佳同时逼近的特征定理 ,并由此导出了最佳同时逼近的交错定理和强唯一性定理     

Interface Assets:Uncontrolled Resources of Competitive Advantage

The purpose of strategic management is to produce knowledge of,to understand and to explain how firms achieve and sustain competitive advantages.On the assumption that something beyond firm-controlled resources and industry structure contribute significantly to firm's competitive advantage as well,I propose a new construct of interface assets to integrate all the resources beyond firm-controlled resources and industry structure.I examine the attributes of interface assets and propose four assumptions about ...     

Trace pursuit variable selection for multi-population data

Variable selection is a very important tool when dealing with high dimensional data. However, most popular variable selection methods are model based, which might provide misleading results when the model assumption is not satisfied. Sufficient dimension reduction provides a general framework for model-free variable selection methods. In this paper, we propose a model-free variable selection method via sufficient dimension reduction, which incorporates the grouping information into the selection procedure for multi-population data. Theoretical properties of our selection methods are also discussed. Simulation studies suggest that our method greatly outperforms those ignoring the grouping information.     

简并能级的三阶微扰修正

讨论了简并能级的三阶微扰修正问题,给出了一阶修正和二阶修正简并部分解除情况下的三阶能量修正,也讨论了一阶修正简并未完全解除时的三阶能量修正.