区域人口分布及空间相关性研究——以安徽省为例

通过ARCGIS9.3空间统计平台,结合相关人口指标,利用2000年、2010年安徽省人口普查数据,对安徽省人口分布的全局与局部相关性、人口分布时空演变特征以及人口分布与自然、经济的空间联系进行了实证分析。分析发现,安徽省人口分布存在空间自相关;自然要素,如地形、河流对安徽省人口分布影响较大;人口重心与经济重心的移动轨迹不一致。据此认为,该结论对安徽省的人口经济发展具有对外加大劳动力转移力度,对内加强新农村和家庭农场建设3大启示。     

AN INVESTIGATION OF MOTIVATIONAL BIAS IN SUBJECTIVE PREDICTIVE PROBABILITY DISTRIBUTIONS*

In this paper the problem of conscious motivational bias in the assessment of subjective predictive probability distributions is explored. The primary purpose of this research is to discover how subjects express their bias. Results of an experiment are reported in which subjective distributions were assessed by subjects, first in the absence of a biasing incentive and then in the presence of an incentive to bias upward coupled with an incentive to be “credible.” In the biased task, subjects reported manipulating up to five characteristics of their distribution, such as location, shape, and dispersion. Furthermore, subjects reported using combinations of the characteristics strategically. Dominant strategies included shifting the mode upward and redistributing probability to the left, shifting the mode upward a small amount and redistributing probability to the right, and shifting the mode upward and tightening the distribution. The location of the mode was mentioned first by nearly all subjects, suggesting that they first locate their biased distribution and then manipulate other characteristics to express their bias, need for credibility, and other concerns.     

不同密度处理对吉林省西部地区糜子光合作用的影响

本实验在高密度26万株/hm~2(D_1)、中密度22万株/hm~2(D_2)和低密度18万株/hm~2(D_3)三个密度处理下进行糜子栽培,并且测定了各个生长期内在不同密度处理下糜子的各项光合作用指标。对测定结果进行研究分析表明:栽培密度能够对糜子生育中、后期的叶面积(LAI)、光合速率(Pn)、气孔导度(Gs),蒸腾速率(Tr)等指标具有很大的影响,从而影响了糜子的光合作用能力。在该实验所设定的三个密度处理中,以中密度22万株/hm~2(D_2)处理下的糜子具有最大的光合作用能力。     

The influence of “country of origin” on multinational corporation global strategy: A conceptual framework

This article examines the proposition that MNCs from a particular country are likely to exhibit profile similarities that are distinct from those of MNCs emanating from another country due to differences in home country factors. We call this “country of origin effect” (COE). A generalized framework is presented briefly explaining the nature of relationships among various COE elements that influence MNC strategy. A number of research propositions are offered that postulate the presumed effect of COE elements on MNC strategy and competitive behavior. Finally, suggestions are made as to the implications of this avenue of enquiry for further research as well as guide for management action.     

Multivariate boundary kernels and a continuous least squares principle

Whereas there are many references on univariate boundary kernels, the construction of boundary kernels for multivariate density and curve estimation has not been investigated in detail. The use of multivariate boundary kernels ensures global consistency of multivariate kernel estimates as measured by the integrated mean-squared error or sup-norm deviation for functions with compact support. We develop a class of boundary kernels which work for any support, regardless of the complexity of its boundary. Our construction yields a boundary kernel for each point in the boundary region where the function is to be estimated. These boundary kernels provide a natural continuation of non-negative kernels used in the interior onto the boundary. They are obtained as solutions of the same kernel-generating variational problem which also produces the kernel function used in the interior as its solution. We discuss the numerical implementation of the proposed boundary kernels and their relationship to locally weighted least squares. Along the way we establish a continuous least squares principle and a continuous analogue of the Gauss–Markov theorem.     

Prospect theory for continuous distributions

We extend the original form of prospect theory by Kahneman and Tversky from finite lotteries to arbitrary probability distributions, using an approximation method based on weak-⋆ convergence. The resulting formula is computationally easier than the corresponding formula for cumulative prospect theory and makes it possible to use prospect theory in future applications in economics and finance. Moreover, we suggest a method how to incorporate a crucial step of the “editing phase” into prospect theory and to remove in this way the discontinuity of the original model.

Probabilities as Similarity‐Weighted Frequencies

A decision maker is asked to express her beliefs by assigning probabilities to certain possible states. We focus on the relationship between her database and her beliefs. We show that if beliefs given a union of two databases are a convex combination of beliefs given each of the databases, the belief formation process follows a simple formula: beliefs are a similarity‐weighted average of the beliefs induced by each past case.     

高等学校概率论教学改革的探索与实践

概率论是一门从数量上研究随机现象统计规律性的科学,其研究方法独特,研究领域广泛,内容实际,应用广泛,是高等院校三大基础数学课程之一。但目前高等院校概率论的教学普遍存在课程内容抽象难懂、教学方式单一死板、授课过程枯燥乏味、学生缺乏学习兴趣等问题,从概率论历史化、生活化和直观化对概率论教学进行了探索实践,使课堂教学变得通俗易懂、贴近生活、趣味十足,增进学生对概率论的理解,活跃学生的思维,提高学生的学习兴趣,从而改善教学效果,提高教学质量。     

Equivalence of two tests in varying coefficient partially linear errors in variable model with missing responses

This paper considers two tests on varying coefficient partially linear errors-in-variables models (VCPLM-EV) with missing responses under the linear constraint. The restricted estimator for the parametric component is derived and proven to share asymptotically normal distribution. In order to test the linear constraint, two statistics based on the profile Lagrange multiplier method and the corrected residual sum of squares method respectively, are proposed. It is of interest to obtain that the magnitudes of the two statistics are equal exactly and follow the asymptotical chi-square distribution. This reveals a new type of Wilk’s phenomenon in VCPLM-EV models with missing response. Finally, some numerical examples are carried out to illustrate relevant performances.     

Discriminating among Weibull,log-normal,and log-logistic distributions

In this article, we consider the problem of the model selection/discrimination among three different positively skewed lifetime distributions. All these three distributions, namely; the Weibull, log-normal, and log-logistic, have been used quite effectively to analyze positively skewed lifetime data. In this article, we have used three different methods to discriminate among these three distributions. We have used the maximized likelihood method to choose the correct model and computed the asymptotic probability of correct selection. We have further obtained the Fisher information matrices of these three different distributions and compare them for complete and censored observations. These measures can be used to discriminate among these three distributions. We have also proposed to use the Kolmogorov–Smirnov distance to choose the correct model. Extensive simulations have been performed to compare the performances of the three different methods. It is observed that each method performs better than the other two for some distributions and for certain range of parameters. Further, the loss of information due to censoring are compared for these three distributions. The analysis of a real dataset has been performed for illustrative purposes.