新形势下上海引进外资问题研究

基于新形势下上海引进外资出现的新情况、新问题,通过对上海投资环境、定位和区位的具体分析,建立上海吸引高端外资的系统框架,并提出上海在市场开放方面,应扩大外资进入领域,鼓励外资投向"上海制造"、"上海服务"、"上海创造"的高端产业,依次引导外资的产业结构升级;在投资环境方面,应建立统一和可预见的法制环境,完善社会信用制度,以此维护市场的竞争秩序;在市场准入方面,应放宽行业限制,不断调整和优化利用外资结构。     

Assessing reporting patterns of child sexual abuse within the Catholic Church using discontinuities in model parameter timeseries

Prior to 2002, little was known about sexual abuse within the Catholic Church. After the Boston Globe broke the story about John Geoghan - a priest in the Boston Archdiocese who was accused of abusing numerous children, convicted of one count of indecent assault, and eventually murdered in prison - the Church had many questions to answer. To this end, the United States Conference of Catholic Bishops (USCCB) commissioned John Jay College of Criminal Justice to research the nature and scope, as well as the causes and context of child sexual abuse within the Catholic Church.This research analyzes the data from the John Jay studies using a new quantitative technique, capable of adjusting for distortions introduced by delays in abuse reporting. By isolating discontinuities in model parameter timeseries, we determine changes in reporting patterns occurred during the period 1982-1988. A posteriori to the analysis, we provide some possible explanations for the changes in abuse reporting associated with the change-point. While the scope of this paper is limited to presenting a new methodological approach within the frame of a particular case study, the techniques are more broadly applicable in settings where reporting lag is manifested.     

论高校国防教育的学科定位

随着教育自身的发展和国际局势的变化,高校国防教育呈现出新的时代特色和学科特点,表现为:全球性的视角、多功能的互补和多学科的渗透。高校国防教育处在众多学科的交叉点上,从共性中突出个性,从普遍性中寻找特殊性,是确立学科定位的基本原则。依照主体性原则,高校国防教育应以高校为主体;其次,国防是国防教育的出发点和落脚点,是目的和归宿,因此高校国防教育应以国防为本位;再次,任何领域的教育现象最终都要落实到育人上来,因此,育人是高校国防教育的基础。     

A test for the equality of k medians against the simple tree alternative under right censorship

We consider a test for the equality of k population medians, θ_i i=1,2,….,k, when it is believed a priori, that θ _i: The observations are subject to right censorhip. The distributions of the censoring variables for each population are assumed to be equal. This test is compared with the general k-sample test proposed by Breslow     

TESTS FOR EXPONENTIALITY AGAINST GAMMA ALTERNATIVES USING NORMALIZED WAITING TIMES

In this article, we present some tests for Exponentiality against Gamma alternatives by using normalized waiting times. The test is constructed by using a quadratic form. The asymptotic distribution of the proposed test is derived. The power of the test is computed through Monte Carlo simulation and is compared with Linhart (1965) test, Bain and Engelhardt (1975) test and Keating et al. (1990) test.     

Geeta distribution and its properties

A new discrete distribution defined over all the positive integers and with the name of Geeta distribution is described. It is L-shaped like the logarithmic series distribution, Yule distribution and the discrete Pareto distribution but is far more versatile than them as it has two parameters. It belongs to the classes of location parameter distributions, modified power series distributions, Lagrange series distributions and exponential distributions. Its mean fi, variance a2 and two recurrence formulae for higher central moments are obtained. Convolution theorem and variations in the model with changes in the parameters have been considered. ML estimators, MVU estimators and estimators based of mean and variance and on mean and first frequency have been derived.     

An Empirical Comparison of Estimating Methods for the Ramberg–Osgood EIV Model

The standard tensile test is one of the most frequent tools performed for the evaluation of mechanical properties of metals. An empirical model proposed by Ramberg and Osgood fits the tensile test data using a nonlinear model for the strain in terms of the stress. It is an Error-In-Variables (EIV) model because of the uncertainty affecting both strain and stress measurement instruments. The SIMEX, a simulation-based method for the estimation of model parameters, is powerful in order to reduce bias due to the measurement error in EIV models. The plan of this article is the following. In Sec. 2, we introduce the Ramberg–Osgood model and another reparametrization according to different assumptions on the independent variable. In Sec. 3, there is a summary of SIMEX method for the case at hand. Section 4 is a comparison between SIMEX and others estimating methods in order to highlight the peculiarities of the different approaches. In the last section, there are some concluding remarks.     

On the one-sample location hypothesis for mixed bivariate data

We study a hypothesis testing problem involving the location model suggested by Olkin and Tate (1961). Specifically, we derive a likelihood ratio lest of the associated location hypothesis as an alternative to the conventional method of carrying out separate tests for each of the parameters. A small sample Monte Carlo comparison indicates the general superiority of the former in terms of statistical power. We also comment briefly on the properties of the test.     

Estimation of gaussian mixtures with rotationally invariant covariance matrices

Homoscedastic and heteroscedastic Gaussian mixtures differ in the constraints placed on the covariance matrices of the mixture components. A new mixture, called herein a strophoscedastic mixture, is defined by a new constraint, This constraint requires the matrices to be identical under orthogonal trans¬formations, where different transformations are allowed for different matrices. It is shown that the M-step of the EM method for estimating the parameters of strophoscedastic mixtures from sample data is explicitly solvable using singular value decompositions. Consequently, the EM-based maximum likelihood estimation algorithm is as easily implemented for strophoscedastic mixtures as it is for homoscedastic and heteroscedastic mixtures. An example of a “noisy” Archimedian spiral is presented.     

An extension of bayesian measure of information to regression

This paper extends Lindley's measure of average information to the linear model, E(Y∣ß) = Xß. An expression which quantifies the average amount of information provided by the nxl vector of observations Y about the pxl vector of coefficient parameters ß will be derived. The effect of the structure of the regressor matrix, X, on the information measure is discussed. An information theoretic optimal design is characterized. Some applications are suggested.