Performance of bartlett adjustment for certain likelihood ratio tests

The effectiveness of Bartlett adjustment, using one of several methods of deriving a Bartlett factor, in improving the chi-squared approximation to the distribution of the log likelihood ratio statistic is investigated by computer simulation in three situations of practical interest:tests of equality of exponential distributions, equality of normal distributions and equality of coefficients of variation of normal distributions.     

对中国大陆经济增长竞争力排名的分析

本文通过对世界经济论坛(WEF)历年全球竞争力报告的分析,指出2002年以来中国大陆经济增长竞争力(GCI)排名下滑是客观存在的。通过研究参加排名的国家和地区数量的变动对中国大陆经济竞争力排名的影响,以及GCI各层子指标变化对中国大陆经济竞争力排名下滑的影响,本文指出了我国经济竞争力排名下滑的深层原因。     

科学发展观与深化政府综合统计体制改革

 内容提要：目前我国政府综合统计存在难以与时俱进地满足政府调控管理需求、抗干扰能力不够强、基层数据失真风险越来越高等一系列问题，已不能很好地适应在全党、全国贯彻落实科学发展观中担负的使命要求。究其原因，本文认为其核心问题是相关管理体制和制度设计不合理、不规范、缺乏与时俱进的能力。要解决这些问题必须以科学发展观为指引，依法治统为重点，治标与治本相结合，在建立国家权威性协调组织、推进政绩考核评估方法完善、缩减基层工作量以及依法规范国家统计需求和统计体系设计管理方面做切实有效的工作。     

外商直接投资区域差异及影响因素的比较研究

20世纪90年代以来,我国利用外商直接投资进入迅速增长时期,但区域间FDI差异不断扩大成为不可争辩的事实。本文尝试从数量和质量两个方面对我国地级城市间FDI差异进行对比分析发现：1993-2008年我国城市FDI数量和质量均有大幅提升,但城市间FDI差异较大,其中数量差异远大于质量差异,从FDI差异变动趋势看,数量差异和质量差异均呈下降趋势。通过面板GMM估计发现城市经济发展水平、FDI滞后效应以及WTO制度变化对FDI数量和质量均产生显著正向影响,工资水平影响是负向的。但分时段估计发现,随着时间推移,工资水平与FDI项目规模呈显著正向关系,即工资水平提高有利于提升一个城市利用外资平均规模,第三产业比重显著影响FDI数量规模。     

基于发展权价值评估视角的农地经营权流转定价方法研究

变更农地用途和开发利用强度是农地内部发展权的物质载体,也是发挥其价值与功用的物质内容,农地内部发展权物质要素的价值形态就是农地内部发展权的价值构成。基于此视角,提出一套农地经营权流转定价模型,该模型能够提离出因土地适度规模化经营、提高土地利用率以及在不改变土地农用属性前提下变更农地用途结构带来的增值收益,并将其纳入到实际交易价格中,以实现土地内部发展权内在价值的外在价格化,重新调整和优化交易双方的收益分配方式。     

On selection biases with prediction rules formed from gene expression data

There has been ever increasing interest in the use of microarray experiments as a basis for the provision of prediction (discriminant) rules for improved diagnosis of cancer and other diseases. Typically, the microarray cancer studies provide only a limited number of tissue samples from the specified classes of tumours or patients, whereas each tissue sample may contain the expression levels of thousands of genes. Thus researchers are faced with the problem of forming a prediction rule on the basis of a small number of classified tissue samples, which are of very high dimension. Usually, some form of feature (gene) selection is adopted in the formation of the prediction rule. As the subset of genes used in the final form of the rule have not been randomly selected but rather chosen according to some criterion designed to reflect the predictive power of the rule, there will be a selection bias inherent in estimates of the error rates of the rules if care is not taken. We shall present various situations where selection bias arises in the formation of a prediction rule and where there is a consequent need for the correction of this bias. We describe the design of cross-validation schemes that are able to correct for the various selection biases.     

劳动力成本上升与中国制造业转移

制造业合理有序的转移对于我国经济的稳定平衡发展具有重要意义。本文使用1998-2013年中国工业企业数据库加总得到的城市层面制造业数据和最低工资代表的劳动力成本数据,首次考察了最低工资与制造业空间分布的因果关系。研究结果表明,最低工资标准的提高降低了城市制造业产值的份额、就业人数份额和规模以上企业数目份额,并推动制造业就近转移。同时,最低工资对制 造业份额的影响存在着明显的异质性,资本密度越高和国有企业占比越多的地区制造业份额受影响越小。进一步的机制检验发现,最低工资标准的上升抑制新企业的设立,促进企业跨区域资本配置和推动企业退出。本文的研究结论有助于厘清劳动力成本上升对制造业空间分布的影响效应,为制造业在区域间的分布和转移提供了重要的政策借鉴。     

生产性服务业集聚与中国企业出口生存——考虑异质性和传导机制的分析

本文以生产性服务业集聚的出口传导效应为切入点，采用我国222个城市数据和微观工业企业数据，通过Cloglog模型研究了生产性服务业集聚对企业出口生存的影响并进行了异质性和传导机制的扩展分析。研究发现：生产性服务业集聚通过专业化分工外溢、综合成本节约效应降低企业面临的出口风险，提高出口生存的概率，但上述效应表现出明显的滞后性；高端生产性服务业集聚对延长企业出口持续时间具有显著的正向效应，而低端生产性服务业集聚由于“拥挤效应”阻碍了企业的出口生存和可持续性，内资企业和非国有企业表现得尤为突出；同时，生产性服务业集聚的影响具有显著的地区异质性，高端生产性服务业集聚显著降低了东部地区企业的出口风险，低端生产性服务业集聚对提升西部地区企业出口成功概率的作用更大；此外，我国生产性服务业集聚的特征使得多样化集聚成为影响企业出口生存的主要机制，专业化集聚的作用相对较小。本研究有助于更全面地认识生产性服务业集聚影响我国企业出口生存的作用机制，对政府管理者更加精准与科学地制定服务业发展和对外开放政策具有积极的现实意义。     

On symmetric (69,17,4)-designs admitting an action of Frobenius groups

The aim of this paper is to achieve the complete classification of (69,17,4)-designs admitting an action of any Frobenius group of automorphisms the kernel of which is isomorphic to one of the cyclic groups of order 13, 17 and 23. A positive result can be got only in the case of the nonabelian group of order 39, where the cyclic group of order 3 fixes exactly 9 points.     

中国海洋经济区域竞争力测度指标体系研究

在解析海洋经济核心特征和海洋经济生产函数、明晰海洋经济竞争力概念的基础上,构建了一套包括发展基础、发展环境和业绩表现3大维度、资源环境等9个方面和62项具体指标的中国海洋经济区域竞争力测度指标体系。利用2011-2012年数据对中国沿海11个地区进行试测之后发现,测度结果符合中国沿海地区海洋经济发展竞争的现实,具有较高效度和信度,可指导沿海各地海洋经济的竞争发展。     

On the Correlation Structure of Gaussian Copula Models for Geostatistical Count Data

We describe a class of random field models for geostatistical count data based on Gaussian copulas. Unlike hierarchical Poisson models often used to describe this type of data, Gaussian copula models allow a more direct modelling of the marginal distributions and association structure of the count data. We study in detail the correlation structure of these random fields when the family of marginal distributions is either negative binomial or zero‐inflated Poisson; these represent two types of overdispersion often encountered in geostatistical count data. We also contrast the correlation structure of one of these Gaussian copula models with that of a hierarchical Poisson model having the same family of marginal distributions, and show that the former is more flexible than the latter in terms of range of feasible correlation, sensitivity to the mean function and modelling of isotropy. An exploratory analysis of a dataset of Japanese beetle larvae counts illustrate some of the findings. All of these investigations show that Gaussian copula models are useful alternatives to hierarchical Poisson models, specially for geostatistical count data that display substantial correlation and small overdispersion.     

A frequentist understanding of sets of measures

We present a mathematical theory of objective, frequentist chance phenomena that uses as a model a set of probability measures. In this work, sets of measures are not viewed as a statistical compound hypothesis or as a tool for modeling imprecise subjective behavior. Instead we use sets of measures to model stable (although not stationary in the traditional stochastic sense) physical sources of finite time series data that have highly irregular behavior. Such models give a coarse-grained picture of the phenomena, keeping track of the range of the possible probabilities of the events. We present methods to simulate finite data sequences coming from a source modeled by a set of probability measures, and to estimate the model from finite time series data. The estimation of the set of probability measures is based on the analysis of a set of relative frequencies of events taken along subsequences selected by a collection of rules. In particular, we provide a universal methodology for finding a family of subsequence selection rules that can estimate any set of probability measures with high probability.     

Identification of the important parameters in thermal building simulation models

Two parameter screening techniques, a sequential bifurcation technique and a factorial sampling method, have been applied to a building thermal model, used to predict thermal comfort performance of a building in its design stage. Combined application of both screening methods revealed a set of 12 important model parameters out of a total of 81, explaining 94% of the variability in the model output. These important parameters were identified by the factorial sampling method on the basis of 246 model evaluations, while sequential bifurcation only needed 52 evaluations. However, the factorial sampling scheme was effective in identifying of not only the important parameters, but also the directions of parameter main effects and the severity of interaction effects. This additional information showed that isolated application of the sequential bifurcation method would have been unreliable, as satisfaction of the inherent assumptions could not be guaranteed. Only on the basis of proper knowledge of the sign of the parameter main effects, adequate clustering of important parameters and transformation of the model output, all obtained from the results of the factorial sampling scheme, reliable and economic application of sequential bifurcation was possible.     

能源消费结构统计特征研究

采用移动平均、HP滤波、VAR模型等方法对中国能源消费结构的循环及趋势特征进行研究,结果表明：化石能源消费对新能源消费影响通过GDP波动而发生作用,强化能源利用效率,维持GDP的稳定增长有助于中国能源消费结构优化,克服循环因素波动的影响。从强化提升新能源消费水平的角度看,煤炭／石油消费量的上升会拉动新能源／天然气消费量的增加,而新能源消费量上升会抑制煤炭／石油消费量的上升。因此,在中国能源消费结构上,新能源与煤炭／石油之间存在一种制衡机制,这也印证了中国产业政策取向和能源消费结构优化政策的合理性。基于此,针对性的提出了相关能源消费结构优化对策。     

Stability of Bayesian decisions

Stability of a Bayes decision is analysed with respect to small changes of the probability measure on the space of the states of nature. The problem leads to the study of continuity aspects of the infimum of the Bayes functional. These are approached through the epigraphical convergence of integral functionals as the minimal setting for convergence of infima.     

塔里木河流域天然植被生态水权及其计量研究

塔里木河流域天然植被退化等生态环境问题主要源于天然植被生态水权内涵界定模糊与缺少计量和分配,为此界定了天然植被生态水权,确定了计量方法与模型,计算了天然植被生态水权需求。研究表明:天然植被生态水权的实际主体和执行主体及其所有权等权利和承担的责任的明确界定,成为生态水权分配的权责保证,而且天然植被生态水权需求计量成为生态水权分配的基础;塔河流域天然植被生态水权需求为61.598亿m3,主要集中在干流,年内需求又在6-9月和3-5月;除阿克苏河流域以草地生态水权需求为主外,其它流域天然植被生态水权需求都以草地和林地生态水权需求为主,其中正常生长天然植被生态水权需求又占主导地位,这成为流域绿洲生态水权时空分配的基础。     

Risk of Error and the Kappa Coefficient of a Binary Diagnostic Test in the Presence of Partial Verification

The accuracy of a binary diagnostic test is usually measured in terms of its sensitivity and its specificity, or through positive and negative predictive values. Another way to describe the validity of a binary diagnostic test is the risk of error and the kappa coefficient of the risk of error. The risk of error is the average loss that is caused when incorrectly classifying a non-diseased or a diseased patient, and the kappa coefficient of the risk of error is a measure of the agreement between the diagnostic test and the gold standard. In the presence of partial verification of the disease, the disease status of some patients is unknown, and therefore the evaluation of a diagnostic test cannot be carried out through the traditional method. In this paper, we have deduced the maximum likelihood estimators and variances of the risk of error and of the kappa coefficient of the risk of error in the presence of partial verification of the disease. Simulation experiments have been carried out to study the effect of the verification probabilities on the coverage of the confidence interval of the kappa coefficient.     

A simulation study of five biased estimators for straight line regression

Five biased estimators of the slope in straight line regression are considered. For each, the estimate of the “bias parameter”, k, is a function of N, the number of observations, and [rcirc]² , the square of the least squares estimate of the standardized slope, β. The estimators include that of Farebrother, the ridge estimator of Hoerl, Kennard, and Baldwin, Vinod's shrunken estimators., and a new modification of one of the latter. Properties of the estimators are studied for 13 combinations of N and 3. Results of simulation experiments provide empirical evidence concerning the values of means and variances of the biased estimators of the slope and estimates of the “bias parameter”, the mean square errors of the estimators, and the frequency of improvement relative to least squares. Adjustments to degrees of freedom in the biased regression analysis of variance table are also considered. An extension of the new modification to the case of p> 1 independent variables is presented in an Appendix.     

Structural inference of the parameters of the heteroscedastic simultaneous equation model

The structural approach of inference for the parameters of a simultaneous equation model with heteroscedastic error variance is investigated in this paper. The joint and the marginal structural distributions for the coefficients of the exogenous variables and the scale parameters of the error variables, and the marginal likelihood function of the coefficients of the endogenous variables have been derived. The estimates are directly obtainable from the structural distribution and the marginal likelihood function of the parameters. The marginal distribution of a subset of coefficients of exogenous variables provides the basis for making inference for a particular subset of parameter of interest.     

中国高等教育投资效益测度方法的设计与应用

高等教育投资效益评价是进一步提高高等教育质量和水平的重要方法。通过从投入系统和产出系统关联的角度,剔除产出测量指标的重复信息和量纲影响的情况下,构造了高等教育投资效益相对评价方法,经实际检验,证明该方法具有客观性。