应用白纸测图技术测绘大比例尺草地群落分布图的探讨

在牧区生产方面 ,大比例尺草地植被分布图是非常重要的基础资料 ,对于划区轮牧、草场轮刈以及草地权属落实等都是最基础的档案 ,然而大比例尺植被图 ( 1:50 0 0 )的测绘却很少有人探讨 ,本文从生产发展需要出发 ,试用测绘学方法白纸测图技术 ,进行 1:50 0 0植物群落分布图的测绘研究 ,此方法可以概括为草群分类、样地选择、界线勾绘、建立控制网、样地扩展、分板实测、联绘成图等步骤     

M-quantile models with application to poverty mapping

Over the last decade there has been growing demand for estimates of population characteristics at small area level. Unfortunately, cost constraints in the design of sample surveys lead to small sample sizes within these areas and as a result direct estimation, using only the survey data, is inappropriate since it yields estimates with unacceptable levels of precision. Small area models are designed to tackle the small sample size problem. The most popular class of models for small area estimation is random effects models that include random area effects to account for between area variations. However, such models also depend on strong distributional assumptions, require a formal specification of the random part of the model and do not easily allow for outlier robust inference. An alternative approach to small area estimation that is based on the use of M-quantile models was recently proposed by Chambers and Tzavidis (Biometrika 93(2):255–268, 2006) and Tzavidis and Chambers (Robust prediction of small area means and distributions. Working paper, 2007). Unlike traditional random effects models, M-quantile models do not depend on strong distributional assumption and automatically provide outlier robust inference. In this paper we illustrate for the first time how M-quantile models can be practically employed for deriving small area estimates of poverty and inequality. The methodology we propose improves the traditional poverty mapping methods in the following ways: (a) it enables the estimation of the distribution function of the study variable within the small area of interest both under an M-quantile and a random effects model, (b) it provides analytical, instead of empirical, estimation of the mean squared error of the M-quantile small area mean estimates and (c) it employs a robust to outliers estimation method. The methodology is applied to data from the 2002 Living Standards Measurement Survey (LSMS) in Albania for estimating (a) district level estimates of the incidence of poverty in Albania, (b) district level inequality measures and (c) the distribution function of household per-capita consumption expenditure in each district. Small area estimates of poverty and inequality show that the poorest Albanian districts are in the mountainous regions (north and north east) with the wealthiest districts, which are also linked with high levels of inequality, in the coastal (south west) and southern part of country. We discuss the practical advantages of our methodology and note the consistency of our results with results from previous studies. We further demonstrate the usefulness of the M-quantile estimation framework through design-based simulations based on two realistic survey data sets containing small area information and show that the M-quantile approach may be preferable when the aim is to estimate the small area distribution function.     

中国省际农村居民收入分配的动态演变:2001-2009年

近十年是我国经济发展变化最快的一段时期,然而“三农”问题日益突出,农民收入是亟待解决的根本问题。本文利用趋同检验、核密度估计以及转移矩阵等方法刻画了我国省际农村居民收入分配的动态演变。实证分析表明,我国贫困地区农村居民收入水平比富裕地区有更高的增长率,从而导致省际农村收入差距呈逐渐缩小趋势,但不同省份的相对收入状况的变动却有所不同。     

基于尾部指数回归方法的CVaR估计以及实证研究

 在险价值VaR是一种非常重要的金融风险度量方法,近期也有很多关于动态VaR以及条件VaR (CVaR) 等方面的研究。根据金融资产的收益率具有重尾特征这一事实,本文假定金融资产收益率服从重尾分布,并假定重尾分布的尾部指数随着收益率发生变化。本文基于尾部指数回归模型对重尾分布的尾部指数进行估计,进而得到收益率尾部数据所服从的条件分布,并首次运用该方法对条件VaR进行估计。本文对沪深300指数进行了实证研究,得到CVaR的估计,并对估计得到的CVaR的预测效果作出检验,并与传统VaR估计方法进行了对比,实证结果发现本文的方法的预测效果更好。     

Description of a subfamily of the discrete pearson system as generalized-binomial distributions

In this paper we prove that a subfamily of distributions of the discrete Pearson, system, containing the Pólya distribution without replacement and hence the hypergeometric distribution, can be described as generalized-binomial distributions, i.e., the distribution of the number of successes which occur in independent trials. It is also shown that the probability of success will necessarily be different in each trial, with the exception of deterministic ones. As a consequence, all the properties of the generalized-binomial distribution will apply to this subfamily. Thus, applications to hypothesis testing and confidence intervals in the Pólya distribution are considered.     

产业融合促进农民共同富裕:作用机理与政策选择

产业融合作为我国农村生产方式的重要变革形态,对农民就业和增收带来深远影响。其机理在于,产业融合发展促进了农村资本要素投入、人力资本积累、农业技术效率提升和生产组织模式创新,不仅提高了资源要素配置效率和农业劳动生产率,而且通过构建合理的利益分享机制,使农民在参与产业链建设中提高了创富能力、实现了收入增长。从农村产业融合发展实践看,反向定制带动了农业产业化模式创新,产业链耦合促进了技术加速扩散,混合经营推动了农村集体经济组织的激活再造,这些新变量和新变化从不同方面、以不同的形式对农民增收致富带来影响。然而,目前我国农村产业融合的整体层次和水平还不高,对农民富裕的促进作用发挥还不够充分,主要原因是生产要素跨界配置面临制度性障碍、农村市场存在功能性缺陷、政府有效激励和规制缺位以及基础服务体系不健全。应加快突破制度障碍、健全市场功能、强化利益分配、夯实基础支撑,促进农村产业深度融合,强化兴农富民带动效应。     

汉英词典100核心词义项分布研究

在认定《现汉》《牛津》《韦氏》等汉英词典是同类词典的基础上，对这些词典中100核心词的义项数目及其分布进行简要对比，发现与《牛津》《韦氏》等英语词典相比，《现汉》等汉语词典在核心词的义项划分方面比较粗疏。     

A Symposium on Unemployment Statistics

Separate Poisson distributions were evaluated via several hypotheses tests for each of the 16 teams in the National Hockey League using 1973–74 goals for and goals against both home and away. After examining independence of goals for and goals against, they in turn were used to explain order of finish for the 16 teams. The results were quite surprising.     

Nonnormality of Linear Combinations of Normal Random Variables

Hamedani and Tata (1975) showed that the bivariate normal distribution is determined uniquely by any countably infinite collection of distinct linear combinations of the variables and by no finite number of them. It is shown here that this characterization of bivariate normal distribution cannot be extended to the multivariate case. More specifically, it is shown that the multivariate normality of subsets (r < n) of the normal variables X ₁, X ₂, …, X_n together with the normality of an infinite number of linear combinations of them do not guarantee the joint normality of these variables.     

C472. The expected value of a conditional variance: An upper bound

The article derives Bartlett corrections for improving the chi-square approximation to the likelihood ratio statistics in a class of symmetric nonlinear regression models. This is a wide class of models which encompasses the t model and several other symmetric distributions with longer-than normal tails. In this paper we present, in matrix notation, Bartlett corrections to likelihood ratio statistics in nonlinear regression models with errors that follow a symmetric distribution. We generalize the results obtained by Ferrari, S. L. P. and Arellano-Valle, R. B. (1996). Modified likelihood ratio and score tests in linear regression models using the t distribution. Braz. J. Prob. Statist., 10, 15–33, who considered a t distribution for the errors, and by Ferrari, S. L. P. and Uribe-Opazo, M. A. (2001). Corrected likelihood ratio tests in a class of symmetric linear regression models. Braz. J. Prob. Statist., 15, 49–67, who considered a symmetric linear regression model. The formulae derived are simple enough to be used analytically to obtain several Bartlett corrections in a variety of important models. We also present simulation results comparing the sizes and powers of the usual likelihood ratio tests and their Bartlett corrected versions.