基于回归分析方法下公共交通对经济增长的影响分析

随着社会经济的发展及人们环保意识的不断增强,公共交通事业的发展及其投资力度不断加大,公共交通在给人们带来方便的同时也在带动着经济的发展.通过扩展的生产函数模型,采用普通最小二乘方法对2003-2012年间的公共交通数据进行估计分析,并找出有异常值的样本点,然后利用稳健MM估计方法进行估计,结果表明公共交通变量对经济的影响具有正相关作用.     

Stability in the presence of degeneracy and error estimation

Received February 10, 1997 / Revised version received June 6, 1998 Published online October 9, 1998     

Some recent and new results on the maximum entropy distribution

This letter concerns the maximum entropy (ME) distribution proposed by Theil and Laitinen (1980); it summarizes some of the results obtained with this distribution and its explores the conditioning of the ME covariance matrix as the number of variables increases.     

基于对偶四元数的卫星信息一致性控制

为了解决航天器控制信息一致性问题,提出了利用对偶四元数来描述对象的位置及姿态信息,实现位置与姿态的统一表述。同时利用信息一致性理论,通过设计航天器间的信息传递模型来解决分布式航天器间的状态同步问题。采用对偶四元数及信息一致性理论为工具,分别给出了位姿同步及跟踪两种控制方法并针对两种信息拓扑模型,以空间交会对接问题进行仿真实验,实验结果表明,在500s以内,卫星的位置及姿态实现了同步及跟踪控制。     

Limit theorems for the median deviation

Summary In this paper, we obtain a strong law and central limit theorem for the median deviation under only very mild smoothness conditions on the underlying distribution. Under an additional condition implied by symmetry, we derive a weak Bahadur representation for the median deviation and establish the asymptotic equivalence of the median deviation and the semi-interquartile range.     

Estimating the efficient price from the order flow: A Brownian Cox process approach

At the ultra high frequency level, the notion of price of an asset is very ambiguous. Indeed, many different prices can be defined (last traded price, best bid price, mid price, etc.). Thus, in practice, market participants face the problem of choosing a price when implementing their strategies. In this work, we propose a notion of efficient price which seems relevant in practice. Furthermore, we provide a statistical methodology enabling to estimate this price from the order flow.     

Boundary Bias Correction for Nonparametric Deconvolution

In this paper we consider the deconvolution problem in nonparametric density estimation. That is, one wishes to estimate the unknown density of a random variable X, say f _X , based on the observed variables Y's, where Y = X + with being the error. Previous results on this problem have considered the estimation of f _X at interior points. Here we study the deconvolution problem for boundary points. A kernel-type estimator is proposed, and its mean squared error properties, including the rates of convergence, are investigated for supersmooth and ordinary smooth error distributions. Results of a simulation study are also presented.     

Estimation of Value at Risk by Extreme Value Methods

Value at Risk (VaR) is defined as a low quantile in the distribution of financial profits and losses. It is the most commonly used measure of market risk in the financial industry. The methods currently used for estimation of VaR have various short comings as they are not aimed specifically at modeling the tails of the distribution of profits and losses; extreme value methods may prove valuable towards improving the current estimation methods. In this paper we give an overview of the current state of the art in applying extreme value methods to financial data and the problems encountered when doing so. We compare the performance of methods currently used for estimation of VaR to the performance of various extreme value methods and outline advantages and drawbacks of the different methods.     

Maximum likelihood estimator for the drift of a Brownian flow

The maximum likelihood estimator for the drift of a Brownian flow on ℝ^d, d ⩾ 2, is found with the assumption that the covariance is known. By approximation of the drift with known functions, the statistical model is reduced to a parametric one that is a curved exponential family. The data is the n‐point motion of the Brownian flow throughout the time interval [0, T]. The asymptotic properties of the MLE are also investigated. Copyright © 2000 John Wiley & Sons, Ltd.     

关于扩散方程漂移系数估计方法的改进

本文提出了一种新的基于扩散过程轨道构造漂移系数样本的方法—对数增量法,通过理论及模拟分析说明了在适当条件下,特别是对于大多数金融数据,基于对数增量法获得的漂移系数估计量的收敛速度及有限样本性质均比基于传统的"直接增量法"所得到的结果要好。