关于知识经济下统计信息创新的思考

以知识和信息为中心,以网络为基础的知识经济时代的到来,给统计信息带来了新的机遇和挑战。统计信息要随着知识经济发展不断进行改革,在统计信息人才、手段、服务内容、核算方法和交流方式等方面进行创新,以适应新时代的需要。     

打造国家统计信息系统平台

国家统计局统一的信息化平台能实现数据的直报,从而大大降低了数据失真的可能性。面临资金的不足,国家统计信息系统的建设采用策略是先由各个省份自己建设,然后再实施各省平台的统一。基于这样的背景,本文通过对部分省市的统计信息系统特点进行了介绍和分析,指出了要打造国家统计信息系统大平台所必须具备的五大特点。     

基于云重心理论的信息价值测评研究

随着科学技术的迅猛发展和信息化进程的加速推进,信息作为一种促进经济和社会发展的资源已经越来越受到人们的重视。首先提出了信息价值的内涵,确立了信息价值测评的主要思想;其次,引入云重心理论的云发生器,用于计算信息价值评估模型的量化值,通过云重心评估模型,可以定量化的计算出信息价值的得分值,从而得到所求的信息价值;最后,以实际企业的调查数据为例,对企业信息价值进行了实际计算,得到了企业信息价值的具体量化值,以便为企业对信息进行决策时提供一种定量方法。     

统计数据、统计安全与统计法治

 本文以《统计违法违纪行为处分规定》的施行为背景,以统计数据质量为切入点,讨论了统计法治问题。文章阐述了统计数据质量与国家统计安全、统计本质与统计法治的关系,并对实现统计法治的途径进行了探讨。     

统计数据失真的动态博弈分析

各类统计主体都是利益主体,都有不同全局利益的个体利益。文章从博弈论和统计理论出发,建立了一个新的统计数据生成模型,首次给出了数据提供方报真与统计部门积极查假的充要条件,也提出了更有针对性的政策建议。     

统计信息系统与统计信息技术

随着现代统计科学体系的不断完善和信息技术的快速渗透,统计信息系统已逐步成熟并普及,催生了统计信息技术研究领域。文章阐释了统计信息系统概念,并给出统计信息技术体系的基本框架。     

Analysis of Type I Error Rates of Univariate and Multivariate Procedures in Repeated Measures Designs

We compared the robustness of univariate and multivariate statistical procedures to control Type I error rates when the normality and homocedasticity assumptions were not fulfilled. The procedures we evaluated are the mixed model adjusted by means of the SAS Proc Mixed module, and Bootstrap-F approach, Brown–Forsythe multivariate approach, Welch–James multivariate approach, and Welch–James multivariate approach with robust estimators. The results suggest that the Kenward Roger, Brown–Forsythe, Welch–James, and Improved Generalized Aprroximate procedures satisfactorily kept Type I error rates within the nominal levels for both the main and interaction effects under most of the conditions assessed.     

A distribution-free test for deprivation dominance

The Raw1sian perspective on social policy pays particular attentionto the least advantaged members of society, but how should "the least advantaged" be identified? The concept of deprivation dominance operationalizes in part the Rawlsian evaluation of the welfare of the least advantaged members of society, but a statistical procedure for testing deprivation dominance is needed. In this paper, we construct a new distribution-free test for deprivation dominance and apply i t to Canadian income survey data     

A strong law of large number for negatively dependent and non identical distributed random variables in the framework of sublinear expectation

Abstract

In this article, in the framework of sublinear expectation initiated by Peng, we derive a strong law of large numbers (SLLN) for negatively dependent and non identical distributed random variables. This result includes and extends some existing results. Furthermore, we give two examples of our result for applications.     

信息技术与统计类课程的实施问题探讨

信息技术与其它学科教学的整合成为当前教改的热点。本文就信息技术与统计类课程整合的实施问题结合多年的教学实践做了较深入的探讨,提出了信息技术与统计类课程整合的基本模式及具体实施方法,希望能给其它的专业课程整合提供一些思路。     

On Variational Bayes Estimation and Variational Information Criteria for Linear Regression Models

Variational Bayes (VB) estimation is a fast alternative to Markov Chain Monte Carlo for performing approximate Baesian inference. This procedure can be an efficient and effective means of analyzing large datasets. However, VB estimation is often criticised, typically on empirical grounds, for being unable to produce valid statistical inferences. In this article we refute this criticism for one of the simplest models where Bayesian inference is not analytically tractable, that is, the Bayesian linear model (for a particular choice of priors). We prove that under mild regularity conditions, VB based estimators enjoy some desirable frequentist properties such as consistency and can be used to obtain asymptotically valid standard errors. In addition to these results we introduce two VB information criteria: the variational Akaike information criterion and the variational Bayesian information criterion. We show that variational Akaike information criterion is asymptotically equivalent to the frequentist Akaike information criterion and that the variational Bayesian information criterion is first order equivalent to the Bayesian information criterion in linear regression. These results motivate the potential use of the variational information criteria for more complex models. We support our theoretical results with numerical examples.     

非对称信息与高频价格变动

高频价格运动对金融市场微观结构具有非常重要的意义。由于高频价格的离散性和不等距变化的特点使得对该类变量建模较为困难,而在理论与实证研究中通常是根据特定的研究目的建立相应的高频价格运动模型。故从金融市场微观结构信息不对称理论出发,结合中国纯限价订单市场的实际情况和对中国市场交易者行为的分析,建立高频价格运动和非对称信息的联合模型,并同时估计和模拟了非对称信息状态和高频价格运动的轨迹。研究发现,知情交易者的比率对交易价格与市场流动性均有显著影响。     

限价订单信息含量分布：理论模型及中国市场实证研究

投资者订单决策过程是研究不完全市场信息释放的逻辑起点。订单的信息分布对市场结构设计有重要的作用。构建非对称环境中投资者订单选择策略模型,并利用高频误差修正模型对理论研究结论进行检验。研究发现中国证券市场订单具有递减信息分布。     

Ratio estimates and fieller's theorem in regression modelling

This paper presents applications of statistical linear models in which a confidence interval is required for the ratio of linear combinations of the model's parameters, Fieller's theorem is used to obtain the solution.     

证券市场信息追随行为理论综述与实证研究

国外对信息追随的研究已经持续了10多年,研究领域从最初的信息追随存在性的证明、贝叶斯假设的合理性发展到信息追随发生原因的探究、信息追随与价格的关系等方面,涉及领域已经较为广泛,但国内专门针对信息追随的研究并不多见。通过实证检验验证中国证券市场信息追随的存在性,研究表明：开放式证券投资基金运作过程中存在显著的信息追随行为,信息追随行为与基金收益密切相关,中国证券市场存在大量的短期投机行为。     

Information,ancillarity, and sufficiency in the presence of nuisance parameters

The Fisher information about parameters of interest (P-information) is invariant with respect to nuisance parameters, and induces an information inequality associated with likelihood factorization. This information inequality provides a natural basis for measuring information loss due to using only a sublikelihood function for inference. In contrast with the global reparametrization of some previous concepts in the literature, the concepts of P-ancillarity and P-sufficiency proposed in this article are characterized by the notion of no pointwise information loss with respect to the parameters of interest. A conditional version of P-sufficiency is also proposed. The asymptotic efficiency of likelihood inference under P-ancillarity or P-sufficiency is outlined.     

HDDA: DataSifter: statistical obfuscation of electronic health records and other sensitive datasets

There are no practical and effective mechanisms to share high-dimensional data including sensitive information in various fields like health financial intelligence or socioeconomics without compromising either the utility of the data or exposing private personal or secure organizational information. Excessive scrambling or encoding of the information makes it less useful for modelling or analytical processing. Insufficient preprocessing may compromise sensitive information and introduce a substantial risk for re-identification of individuals by various stratification techniques. To address this problem, we developed a novel statistical obfuscation method (DataSifter) for on-the-fly de-identification of structured and unstructured sensitive high-dimensional data such as clinical data from electronic health records (EHR). DataSifter provides complete administrative control over the balance between risk of data re-identification and preservation of the data information. Simulation results suggest that DataSifter can provide privacy protection while maintaining data utility for different types of outcomes of interest. The application of DataSifter on a large autism dataset provides a realistic demonstration of its promise practical applications.     

Information in experiments and sufficiency

We define measures of information contained in an experiment which are by-products of the parametric measures of Fisher, Vajda, Mathai and Boekee and the non-parametric measures of Bhattacharyya, Rényi, Matusita, Kagan and Csiszár. We use these measures to compare sufficient experiments according to Blackwell's definition. In particular, we prove that if δ_X and δ_Y are two experiments and δ_X≥δ_Y then l_X≥l_y for all of the above measures.     

Focused Information Criterion and Model Averaging in Quantile Regression

In this article, we study model selection and model averaging in quantile regression. Under general conditions, we develop a focused information criterion and a frequentist model average estimator for the parameters in quantile regression model, and examine their theoretical properties. The new procedures provide a robust alternative to the least squares method or likelihood method, and a major advantage of the proposed procedures is that when the variance of random error is infinite, the proposed procedure works beautifully while the least squares method breaks down. A simulation study and a real data example are presented to show that the proposed method performs well with a finite sample and is easy to use in practice.     

信息非对称下行政体系中职位竞争与权力寻租

信息非对称是行政体系的职位竞争中形成“权力寻租”的主要原因。文章通过研究行政体系的职位竞争中“权力寻租”的形成机理,分析信息在“寻租”形成过程中的意义。研究表明,信息非对称将加剧行政职位晋升的腐败,导致激励机制扭曲。