我国上市公司资本结构决策的实证研究

本在已有资本结构理论研究成果的基础上，对30家沪市上市公司的资本结构进行了实证研究，提出了在我国资本市场环境下优化企业资本结构的对策建议。     

NA序列下经验分布函数的渐近正态性及其应用

本文在NA负相协序列下利用熟知的相依情形的大小块分割的方法,建立了经验分布函数的渐近正态性．作为在可靠性中的应用,得到了生存函数■(x)=P(X＞x)估计的渐近正态性．     

An efficient sampling method for stochastic inverse problems

A general framework is developed to treat inverse problems with parameters that are random fields. It involves a sampling method that exploits the sensitivity derivatives of the control variable with respect to the random parameters. As the sensitivity derivatives are computed only at the mean values of the relevant parameters, the related extra cost of the present method is a fraction of the total cost of the Monte Carlo method. The effectiveness of the method is demonstrated on an example problem governed by the Burgers equation with random viscosity. It is specifically shown that this method is two orders of magnitude more efficient compared to the conventional Monte Carlo method. In other words, for a given number of samples, the present method yields two orders of magnitude higher accuracy than its conventional counterpart.     

上市公司高管薪酬和企业业绩关系研究

本运用我国生物医药上市公司的经验数据考察高管薪酬与企业业绩的关系问题。研究的结果表明高管薪酬水平与企业业绩显正相关，高管团队内的薪酬差距也与企业业绩显正相关，而高管持股则与企业业绩负相关，在统计上不显。因此章建议企业应该考虑股权激励的成本和效果，改善股权激励制度。研究还表明企业追求的目标是规模最大化而不是股东净资产收益率最大化。     

利用排列熵检测近40年华北地区气温突变的研究

运用一种新的动力学突变检测方法——排列熵(permutation entropy，PE)算法，计算并分析了中国华北地区52个站点1960年—2000年逐日平均气温资料的排列熵演化情况，发现中国华北地区气温在20世纪70年代中期、80年代初均发生了较大突变；进一步用经验模态分解(empirical mode decomposition，EMD)方法对排列熵序列进行逐级平稳化处理，结果发现这一地区的气温突变与准10年这一年代际时间尺度的周期变率密切相关，其原因与太阳黑子活动有着密切联系. 关键词： 华北 突变 排列熵算法 经验模态分解     

On the covariance of the level sizes in random recursive trees

In this paper we study the covariance structure of the number of nodes k and l steps away from the root in random recursive trees. We give an analytic expression valid for all k, l and tree sizes N. The fraction of nodes k steps away from the root is a random probability distribution in k. The expression for the covariances allows us to show that the total variation distance between this (random) probability distribution and its mean converges in probability to zero. © 2002 Wiley Periodicals, Inc. Random Struct. Alg., 20: 519–539, 2002     

Profile empirical likelihood for parametric and semiparametric models

This paper introduces a profile empirical likelihood and a profile conditionally empirical likelihood to estimate the parameter of interest in the presence of nuisance parameters respectively for the parametric and semiparametric models. It is proven that these methods propose some efficient estimators of parameters of interest in the sense of least-favorable efficiency. Particularly, for the decomposable semiparametric models, an explicit representation for the estimator of parameter of interest is derived from the proposed nonparametric method. These new estimations are different from and more efficient than the existing estimations. Some examples and simulation studies are given to illustrate the theoretical results. The first author is supported by NNSF projects (10371059 and 10171051) of China. The second author is supported by a grant from The Research Grants Council of the Hong Kong Special Administrative Region, China (#HKU7060/04P). The third author is supported by the University Research Committee of the University of Hong Kong and a grant from the Research Grants Council of the Hong Kong Special Administrative Region, China (Project No. HKU7323/01M).     

Regression quantiles for unstable autoregressive models

This paper investigates regression quantiles (RQ) for unstable autoregressive models. The uniform Bahadur representation of the RQ process is obtained. The joint asymptotic distribution of the RQ process is derived in a unified manner for all types of characteristic roots on or outside the unit circle. It involves stochastic integrals in terms of a sequence of independent and identically distributed multivariate Brownian motions with correlated components. The related L-estimator is also discussed. The asymptotic distributions of the RQ and the L-estimator corresponding to the nonstationary componentwise arguments can be transformed into a function of a normal random variable and a sequence of i.i.d. univariate Brownian motions. This is different from the analysis based on the LSE in the literature. As an auxiliary theorem, a weak convergence of a randomly weighted residual empirical process to the stochastic integral of a Kiefer process is established. The results obtained in this paper provide an asymptotic theory for nonstationary time series processes, which can be used to construct robust unit root tests.     

A strong law of large numbers for generalized random sets from the viewpoint of empirical processes

In this article we prove a strong law of large numbers for Borel measurable nonseparably valued random elements in the case of generalized random sets.

     

Sample path analysis of level crossings for the workload process

We examine level crossings of sample paths of queueing processes and investigate the conditions under which the limiting empirical distribution for the workload process exists and is absolutely continuous. The connection between the density of the workload distribution and the rate of downcrossings is established as a sample path result that does not depend on any stochastic assumptions. As a corollary, we obtain the sample path version of the Takács formula connecting the time and customer stationary distributions in a queue. Defective limiting empirical distributions are considered and an expression for the mass at infinity is derived.This research has been supported in part by NSF Grants ECS-8811003 and DDM-8905638.