中国环境公益诉讼之兴起与走势——基于环境正义与环境诉讼价值进路的分析

在我国,环境污染及其造成的损害日益严重,客观上对损害救济的相关法律提出了变革与发展的要求。然而,传统环境侵权诉讼在原告资格、诉讼事由和诉讼主体——环保团体的诉讼资格方面面临诸多困境。环境公益诉讼在原告的起诉资格、诉讼标的、诉讼事由以及诉讼性质等方面,弥补了传统环境侵权诉讼的缺陷,在实现环境正义、保护环境公益、救济环境损害方面起到了不可替代的作用。     

A hierarchical model for extreme wind speeds

Summary.  A typical extreme value analysis is often carried out on the basis of simplistic inferential procedures, though the data being analysed may be structurally complex. Here we develop a hierarchical model for hourly gust maximum wind speed data, which attempts to identify site and seasonal effects for the marginal densities of hourly maxima, as well as for the serial dependence at each location. A Gaussian model for the random effects exploits the meteorological structure in the data, enabling increased precision for inferences at individual sites and in individual seasons. The Bayesian framework that is adopted is also exploited to obtain predictive return level estimates at each site, which incorporate uncertainty due to model estimation, as well as the randomness that is inherent in the processes that are involved.     

Improving coverage accuracy of nonparametric prediction intervals

Methods are suggested for improving the coverage accuracy of intervals for predicting future values of a random variable drawn from a sampled distribution. It is shown that properties of solutions to such problems may be quite unexpected. For example, the bootstrap and the jackknife perform very poorly when used to calibrate coverage, although the jackknife estimator of the true coverage is virtually unbiased. A version of the smoothed bootstrap can be employed for successful calibration, however. Interpolation among adjacent order statistics can also be an effective way of calibrating, although even there the results are unexpected. In particular, whereas the coverage error can be reduced from O ( n ^-1) to orders O ( n ^-2) and O ( n ^-3) (where n denotes the sample size) by interpolating among two and three order statistics respectively, the next two orders of reduction require interpolation among five and eight order statistics respectively.     

Extreme value models with application to drought data

Summary The exact distributions of the productXY are derived whenX andY are independent random variables and come from the extreme value distribution of Type I, the extreme value distribution of Type II or the extreme value distribution of Type III. Of the, six possible combinations, only three yield closed-form expressions for the distribution ofXY. A detailed application of the results is provided to drought data from Nebraska. The author would like to thank the referees and the Associate Editor for carefully reading the paper and for their great help in improving the paper.     

Linearity of regression for non-adjacent record values

Let X₁,X₂,… be a sequence of iid random variables having a continuous distribution; by R₁,R₂,… denote the corresponding record values. All the distributions allowing linearity of regressions either E(R_m+k|R_m) or E(R_m|R_m+k) are identified.     

试论时间价值观

时间是一种重要的资源。时间价值观是个体以自身的需要为尺度对时间重要性的稳定态度和观念。时间价值观含有时间资源观、时间效率观、时机观、时间顺序观等方面的意义。时间价值观的结构可以有不同的划分。时间价值观受社会文化传统、个体的年龄因素、个体性格、社会环境等因素的影响。心理学对时间价值观的研究在理论上和应用中都有着重要的意义     

选择价值工程改进对象的动态排序模型

从一个复杂系统中,合理地选择重点改进对象,是有效开展价值工程活动的基础。本文在分析最合适区域法存在的问题的基础上,提出选择价值工程改进对象的动态排序模型。     

中国证券业总产出和增加值测算研究

 金融机构总产出和增加值的测算是一项基础性的研究工作。与传统测算方法不同,本文借鉴经济合作和发展组织（OECD）提出的使用者成本法,把证券业视为生产性服务活动,并结合我国的实际情况,从服务的角度初步提出了我国证券业总产出和增加值的测算框架。并提出了未来研究改进的方向。     

抽样调查中估计量的Bootstrap修正及样本量的确定

估计量的精度和样本量的确定是抽样设计中所关心的两个主要问题.在一定条件下,对于简单随机抽样,通过对初级样本的Bootstrap抽样可以提高均值估计量的精度.中心极限定理一直是抽样调查中确定样本量的主要理论依据,基本思想就是将标准正态分布作为给定统计量的近似分布.如果利用Bootstrap方法模拟近似分布,同样可以确定样本量.文章结合具体例子对两种方法确定的样本量进行了对比分析.     

A new estimation method for Weibull-type tails based on the mean excess function

Studying the right tail of a distribution, one can classify the distributions into three classes based on the extreme value index γ$\gamma$. The class γ>0$\gamma >0$ corresponds to Pareto-type or heavy tailed distributions, while γ<0$\gamma <0$ indicates that the underlying distribution has a finite endpoint. The Weibull-type distributions form an important subgroup within the Gumbel class with γ=0$\gamma =0$. The tail behaviour can then be specified using the Weibull tail index. Classical estimators of this index show severe bias. In this paper we present a new estimation approach based on the mean excess function, which exhibits improved bias and mean squared error. The asserted properties are supported by simulation experiments and asymptotic results. Illustrations with real life data sets are provided.