天津滨海新区经济协调发展机制的构建

如何建立区域经济协调机制，促进区域经济的合作与发展，是滨海新区经济发展中面临的重要问题。阐述了区域经济协调机制构建的基础原则。在此基础上，论述了区域经济协调机制的构成要素，提出了滨海新区区域经济协调发展机制的框架。     

平均干扰下的无线传感器网络高效能传输研究

传输功率的调整是当前无线传感器网络进行低功耗优化设计的主要手段之一,但较低的传输功率却又很难保证连通性(因外围节点干扰引入的随机性),较大的传输功率不仅增加能耗而且会对邻近通信节点带来干扰,如果简单地在网络中进行传输功率调整,极易造成相邻通信子网传输功率的相互攀升,从而极大地降低了传输效能。该文从干扰模型分析出发,给出了基于平均干扰下的最优传输功率计算方法,考虑到网络环境的时变性,将该优化传输功率与自适应速率控制机制结合以提高传输效能。仿真结果表明,相比于MCP协议和Basic协议,基于平均干扰下的优化传输功率机制在单比特能耗及平均吞吐率上能够得到更好的性能折中。     

论赛音诺颜部与清朝的关系

论述了喀尔喀蒙古赛音诺颜部与清朝关系的建立,及其在清统治西北边疆中的作用,分析了清朝对其政策实行的背景,及赛音诺颜部贵族在稳定北部边疆和统一新疆过程中的作用.     

存在时变方差的股指期货最佳套期保值比率计算

在Cecchetti等人研究的基础上，给出存在时变方差的情形下，利用最大效用法计算股指期货套期保值比率的方法，推导出用矩阵表达的形式，并对相关参数进行估计。     

边塞诗与历代诗人的青藏高原情结

历代边塞诗人之所以怀有浓厚的青藏高原情结，把关注的目光投向青海这块古老而年轻的西陲边地，创作出了大量反映青海风貌的诗篇，就在于它所具有的独特的历史文化特质和多样的高原生态环境。作为民族友好的见证地、物产丰富的宝地、兵家相争的要冲、神话传说的发祥地——青海，留给了诗人们太多思考和想象的空间，并成为他们不竭的诗歌创作之源。     

基于分形理论下的股票市场有效性研究

利用分形理论对我国股市的有效性进行研究,研究的对象包括:上证A股指数、深成A股指数、上证B股指数和深证B股指数。首先通过Kolmogorov-Smirnov检验法来检验中国股市收益率的正态性,得出收益率不是正态分布的,在此基础上,利用分形理论中的R/S分析法来研究中国股市的有效性。研究的结果表明,中国股市具有明显的分形结构,因此不是有效市场,A股市场相对于B股市场来说是比较有效的,B股市场的可预测性大于A股市场。同时,还进一步研究了中国股票市场的非周期循环。     

提高大学生英语阅读效率的研究与实践

本文试图在“图式理论”及实验研究的基础上勾画出对我国大学生进行英语教学的框架，并提出了一些为提高学生英语阅读效率所采用的方法及几种类型的练习。经实验证明，如果学生掌握了一些阅读技巧，就会提高阅读理解能力，成为独立、高效的读者。     

TWO-STAGE SUPPORT ESTIMATION

This paper presents a two‐stage procedure for estimating the conditional support curve of a random variable X, given the information of a random vector X. Quantile estimation is followed by an extremal analysis on the residuals for problems which can be written as regression models. The technique is applied to data from the National Bureau of Economic Research and US Census Bureau's Center for Economic Studies which contain all four‐digit manufacturing industries. Simulation results show that in linear regression models the proposed estimation procedure is more efficient than the extreme linear regression quantile.     

On difference-based variance estimation in nonparametric regression when the covariate is high dimensional

Summary.  We consider the problem of estimating the noise variance in homoscedastic nonparametric regression models. For low dimensional covariates t  ∈  R ^d ,  d =1, 2, difference-based estimators have been investigated in a series of papers. For a given length of such an estimator, difference schemes which minimize the asymptotic mean-squared error can be computed for d =1 and d =2. However, from numerical studies it is known that for finite sample sizes the performance of these estimators may be deficient owing to a large finite sample bias. We provide theoretical support for these findings. In particular, we show that with increasing dimension d this becomes more drastic. If d 4, these estimators even fail to be consistent. A different class of estimators is discussed which allow better control of the bias and remain consistent when d 4. These estimators are compared numerically with kernel-type estimators (which are asymptotically efficient), and some guidance is given about when their use becomes necessary.     

Propriétés statistiques des copules de valeurs extrêmes bidimensionnelles

Let (X, Y) be a bivariate random vector whose distribution function H(x, y) belongs to the class of bivariate extreme-value distributions. If F₁ and F₂ are the marginals of X and Y, then H(x, y) = C{F₁(x),F₂(y)}, where C is a bivariate extreme-value dependence function. This paper gives the joint distribution of the random variables Z = {log F₁(X)}/{log F₁(X)F₂(Y)} and W = C{F₁{(X),F₂(Y)}. Using this distribution, an algorithm to generate random variables having bivariate extreme-value distribution is présentés. Furthermore, it is shown that for any bivariate extreme-value dependence function C, the distribution of the random variable W = C{F₁(X),F₂(Y)} belongs to a monoparametric family of distributions. This property is used to derive goodness-of-fit statistics to determine whether a copula belongs to an extreme-value family.