Smoothing for discrete-valued time series

We deal with smoothed estimators for conditional probability functions of discrete-valued time series { Y_t } under two different settings. When the conditional distribution of Y_t given its lagged values falls in a parametric family and depends on exogenous random variables, a smoothed maximum (partial) likelihood estimator for the unknown parameter is proposed. While there is no prior information on the distribution, various nonparametric estimation methods have been compared and the adjusted Nadaraya–Watson estimator stands out as it shares the advantages of both Nadaraya–Watson and local linear regression estimators. The asymptotic normality of the estimators proposed has been established in the manner of sparse asymptotics, which shows that the smoothed methods proposed outperform their conventional, unsmoothed, parametric counterparts under very mild conditions. Simulation results lend further support to this assertion. Finally, the new method is illustrated via a real data set concerning the relationship between the number of daily hospital admissions and the levels of pollutants in Hong Kong in 1994–1995. An ad hoc model selection procedure based on a local Akaike information criterion is proposed to select the significant pollutant indices.     

3-状态部分2-树网络可靠度的一个多项式时间算法

本文利用3-状态设备网络可靠度计算归约公式,结合Wald.J.A.-Colbourn C.J.[1]算法(简称为W-C算法2),给出了3-状态部分2-树网络可靠度的一个多项式时间算法.     

Shrinkage Structure of Partial Least Squares

Partial least squares regression (PLS) is one method to estimate parameters in a linear model when predictor variables are nearly collinear. One way to characterize PLS is in terms of the scaling (shrinkage or expansion) along each eigenvector of the predictor correlation matrix. This characterization is useful in providing a link between PLS and other shrinkage estimators, such as principal components regression (PCR) and ridge regression (RR), thus facilitating a direct comparison of PLS with these methods. This paper gives a detailed analysis of the shrinkage structure of PLS, and several new results are presented regarding the nature and extent of shrinkage.     

A further note on a theorem on the difference of the generalized inverses of two nonnegative definite matrices

Andrews and Phillips (1986) gave a simplified proof for the result that established the nonnegative definiteness of the difference of the Moore-Penrose inverses of two nonoegative definite matrices, a result originally due to Milliken and Akdeniz (1977), The purpose of this paper is to offer a simple proof for a generalization of this result,     

要约收购分类研究

从收购方发出收购要约是自愿还是法律强制规定等几个角度对要约收购分类进行详细阐述，使各国在对要约收购方式立法时能根据本国国情有所选择、有所侧重，从而将资源优化配置与中小股东权益保护相结合，实现效率与公平在立法及实施上的平衡。     

AN EXACT CONDITIONAL TEST FOR COVARIANCE SELECTION MODELS

An exact conditional test is developed for testing the absence of an edge in a graphical covariance selection model and is shown to be equivalent to a test based on the partial correlation coefficient. An example is given.     

一个偏微分方程的解与Laguerre多项式

由两种方法求解一个偏微分方程，得到了一个算子公式和关于Ｌａｇｕｅｒｒｅ多项式的两种微分表达式。     

基于偏时域相干算法的一种信号分析系统

本文提出将偏时域相干算法应用于一种实时信号分离系统，简要介绍了该系统的基本原理、系统的总体设计方案及该系统的适用条件．计算机仿真结果表明了该系统的有效性．     

Law of iterated logarithm and almost sure limit points for random sums

Let {X_n,n≥1} be a sequence of independent identically distributed (i.i.d) random variables with a common distribution function F. When F belongs to the domain of partial attraction of a Semi-Stable law with index ,0<<2, we give complete solution to the results of R. Vasudeva and G. Divanji [Law of iterated logarithm for random subsequences, Statist. Probab. Lett. 12 (1991) 189–194], where they obtained Chover’s form of the law of iterated logarithm for random subsequences. Further, we extended the situation in obtaining almost sure limit points for random subsequences.     

含时滞的偏泛函微分方程解的稳定性

采用不等式估值方法 ,对含时滞的偏泛函微分方程解的稳定性进行了讨论 ,获得了零解渐近稳定的简洁判据