苏州市污染物减排推进机制优化的实证研究

通过对苏州市经济发展水平与环境质量的相关数据进行处理,求出苏州市环境库兹涅茨曲线的理论峰值,认为在环境库兹涅茨曲线的拐点出现之前,如果苏州市不抓住机遇对污染物减排推进机制进行优化,将会难以实现苏州市环境库兹涅茨曲线的理想状态;同时探讨了如何通过经济和环境的政策创新,促使苏州市尽快在当前特定的历史阶段跨越环境库兹涅茨曲线的拐点;这一结论也适用于国内其他同类城市推出污染物减排机制的优化。     

A score test for overdispersion in Poisson regression based on the generalized Poisson-2 model

Overdispersion is a common phenomenon in Poisson modeling. The generalized Poisson (GP) regression model accommodates both overdispersion and underdispersion in count data modeling, and is an increasingly popular platform for modeling overdispersed count data. The Poisson model is one of the special cases in the collection of models which may be specified by GP regression. Thus, we may derive a test of overdispersion which compares the equi-dispersion Poisson model within the context of the more general GP regression model. The score test has an advantage over the likelihood ratio test (LRT) and over the Wald test in that the score test only requires that the parameter of interest be estimated under the null hypothesis (the Poisson model). Herein, we propose a score test for overdispersion based on the GP model (specifically the GP-2 model) and compare the power of the test with the LRT and Wald tests. A simulation study indicates the proposed score test based on asymptotic standard normal distribution is more appropriate in practical applications.     

A Discrete Distribution Arising as a Solution of a Linear Difference Equation: Extension of the Non Central Negative Binomial Distribution

This article considers a discrete distribution that arises as the dominant solution of a linear difference equation. Basic properties and various chance mechanisms that lead to this distribution are given. In particular, its formulation as a weighted distribution and a mixed Poisson process are proposed. Parameter estimation by (a) using a combination of observed frequencies and moments and (b) maximum likelihood are examined. An example of goodness of fit is considered.     

On Infinitely Divisible Exponential Dispersion Model Related to Poisson-Exponential Distribution

We construct a univariate exponential dispersion model comprised of discrete infinitely divisible distributions. This model emerges in the theory of branching processes. We obtain a representation for the Lévy measure of relevant distributions and characterize their laws as Poisson mixtures and/or compound Poisson distributions. The regularity of the unit variance function of this model is employed for the derivation of approximations by the Poisson-exponential model. We emphasize the role of the latter class. We construct local approximations relating them to properties of special functions and branching diffusions.     

Whither jackknifing in stein-rule estimation

In multi-parameter ( multivariate ) estimation, the Stein rule provides minimax and admissible estimators , compromising generally on their unbiasedness. On the other hand, the primary aim of jack-knifing is to reduce the bias of an estimator ( without necessarily compromising on its efficacy ), and, at the same time, jackknifing provides an estimator of the sampling variance of the estimator as well. In shrinkage estimation ( where minimization of a suitably defined risk function is the basic goal ), one may wonder how far the bias-reduction objective of jackknifing incorporates the dual objective of minimaxity ( or admissibility ) and estimating the risk of the estimator ? A critical appraisal of this basic role of jackknifing in shrinkage estimation is made here. Restricted, semi-restricted and the usual versions of jackknifed shrinkage estimates are considered and their performance characteristics are studied . It is shown that for Pitman-type ( local ) alternatives, usually, jackkntfing fails to provide a consistent estimator of the ( asymptotic ) risk of the shrinkage estimator, and a degenerate asymptotic situation arises for the usual fixed alternative case.     

股权相对分散化趋势下双层股权制度的适用问题

双层股权制度有助于改善缺乏弹性的股权结构,保障公司创始人对公司管理权的控制。由于违反了“一股一权”原则,双层股权制度造成公司管理权与公司现金流量请求权的分离,可能诱发更大的公司道德风险,使中小股东的权益保护面临更为严峻的挑战。当前公司股权结构呈现出相对分散化的大趋势,使中小股东进行联合维权的难度进一步加大,有必要完善双层股权制度中保护中小股东的相关规范,切实保障中小股东的合法权益。     

略论美国排污法律制度及对我国的启示

美国作为西方最发达的国家之一,在发展自身工业的同时十分重视对国内的环境保护。早在20世纪60年代美国就先后通过了水污染治理法、清洁水法、水污染防治法等一系列法律。他山之石可以攻玉,可以从美国的先进立法经验中得到适当的经验,并与我国的实际情况相结合,探讨建立有中国特色的水污染防治体系。     

ADJUSTING RESIDUALS IN ESTIMATION OF DISPERSION EFFECTS

This paper studies a method of adjusting the ordinary least squares residuals, when estimating and comparing dispersions, at various levels of factors in a replicated factorial experiment. Using a general dispersion model, theoretical results demonstrate the benefits of the method of adjusting residuals. An illustrative example is included.     

Profile likelihood-based confidence interval for the dispersion parameter in count data

The importance of the dispersion parameter in counts occurring in toxicology, biology, clinical medicine, epidemiology, and other similar studies is well known. A couple of procedures for the construction of confidence intervals (CIs) of the dispersion parameter have been investigated, but little attention has been paid to the accuracy of its CIs. In this paper, we introduce the profile likelihood (PL) approach and the hybrid profile variance (HPV) approach for constructing the CIs of the dispersion parameter for counts based on the negative binomial model. The non-parametric bootstrap (NPB) approach based on the maximum likelihood (ML) estimates of the dispersion parameter is also considered. We then compare our proposed approaches with an asymptotic approach based on the ML and the restricted ML (REML) estimates of the dispersion parameter as well as the parametric bootstrap (PB) approach based on the ML estimates of the dispersion parameter. As assessed by Monte Carlo simulations, the PL approach has the best small-sample performance, followed by the REML, HPV, NPB, and PB approaches. Three examples to biological count data are presented.     

Empirical study of some non-parametric tests for dispersion of correlated data

Results of a computer simulation study of power and robustness of three competitor tests for comparing scales, for use with correlated data: Rothstein, Richardson and Bell (RRB), Arvesen, and Pitman, are presented. It is found that unless one could ímprove the approximate null distributions for Arvesen's and Pitman's test, RRB's procedure is best, having simulated probabilities of Type I error closest to the test's nominal α and being reasonably robust and powerful, for all distributions considered.