青岛一套表的实践与经验

 企业统计一套表一直是统计制度方法改革和实践中的焦点问题。本文通过对青岛市统计局企业一套表制度实施情况的案例分析,系统界定了企业一套表的概念和内涵,全面展现了企业一套表的运作过程,客观分析了制约企业一套表实施的主要原因,并提出了在现阶段实施企业统计一套表的条件和要求。     

大股东控制影响公司现金持有量的实证分析

 本文结合我国上市公司所面临的内部治理机制特点及外部治理环境,从大股东行为的视角对公司现金持有量的影响因素进行实证分析。在加入年度控制变量、行业控制变量和公司财务特征控制变量后,对三项反映大股东行为特征的因素,即大股东持股比例、大股东属性和制度环境因素对公司现金持有量的影响进行了检验。结果表明,第一大股东持股比例较高的公司持有较多的现金,大股东的高持股比例是其占用企业资金侵占中小股东利益的基础。与国有企业相比,民营企业因遭受较强的外部融资约束而持有较高水平的现金。此外,制度环境的发展程度与公司现金持有水平正相关,表明制度环境较好地区的公司持有较多的现金。     

Analysis of supersaturated designs via the Dantzig selector

A supersaturated design is a design whose run size is not enough for estimating all the main effects. It is commonly used in screening experiments, where the goals are to identify sparse and dominant active factors with low cost. In this paper, we study a variable selection method via the Dantzig selector, proposed by Candes and Tao [2007. The Dantzig selector: statistical estimation when p$p$ is much larger than n$n$. Annals of Statistics 35, 2313–2351], to screen important effects. A graphical procedure and an automated procedure are suggested to accompany with the method. Simulation shows that this method performs well compared to existing methods in the literature and is more efficient at estimating the model size.     

中国金融状况指数的构建及预测能力研究

本文首先选取利率、汇率、股票价格和社会融资规模四个金融变量,建立SVAR模型确定变量权重,构建了量化我国金融状况整体松紧程度的中国金融状况指数.其次,基于已构建指数,引入谱分析方法研究发现:中国金融状况指数与宏观经济景气指数中的一致指数、环比和同比CPI三个指标之间均存在39个月的耦合震荡周期,且中国金融状况指数领先三个指标的期数分别为1.91、0.44和5.5个月,对应一致性统计量的值依次为0.94、0.97和0.96,均接近于1,说明中国金融状况指数对宏观经济景气指数中的一致指数以及对通货膨胀均具有先导性和强相关性,可作为其他宏观经济指标的先行指标.     

An Efficient Estimation for Switching Regression Models: A Monte Carlo Study

This article investigates an efficient estimation method for a class of switching regressions based on the characteristic function (CF). We show that with the exponential weighting function, the CF-based estimator can be achieved from minimizing a closed form distance measure. Due to the availability of the analytical structure of the asymptotic covariance, an iterative estimation procedure is developed involving the minimization of a precision measure of the asymptotic covariance matrix. Numerical examples are illustrated via a set of Monte Carlo experiments examining the implementation, finite sample property and the efficiency of the proposed estimator.     

On the Preliminary Test Backfitting and Speckman Estimators in Partially Linear Models and Numerical Comparisons

Przystalski and Krajewski (2007 Przystalski , M. , Krajewski , P. ( 2007 ). Constrained estimators of treatment parameters in semiparametric models . Statist. Probab. Lett. 77 : 914 – 919 .[Crossref], [Web of Science ®] , [Google Scholar]) proposed the restricted backfitting (RBCF) estimator and restricted Speckman (RSPC) estimator for the treatment effects in a partially linear model when some additional exact linear restrictions are assumed to hold. In this article, we introduce the preliminary test backfitting (PTBCF) estimator and preliminary test Speckman (PTSPC) estimator when the validity of the restrictions is suspected. Performances of the proposed estimators are examined with respect to the mean squared error (MSE) criterion. In addition, numerical behaviors of the proposed estimators are illustrated and compared via a Monte Carlo simulation study.     

Case–control genome-wide joint association study using semiparametric empirical model and approximate Bayes factor

We propose a semiparametric approach for the analysis of case–control genome-wide association study. Parametric components are used to model both the conditional distribution of the case status given the covariates and the distribution of genotype counts, whereas the distribution of the covariates are modelled nonparametrically. This yields a direct and joint modelling of the case status, covariates and genotype counts, and gives a better understanding of the disease mechanism and results in more reliable conclusions. Side information, such as the disease prevalence, can be conveniently incorporated into the model by an empirical likelihood approach and leads to more efficient estimates and a powerful test in the detection of disease-associated SNPs. Profiling is used to eliminate a nuisance nonparametric component, and the resulting profile empirical likelihood estimates are shown to be consistent and asymptotically normal. For the hypothesis test on disease association, we apply the approximate Bayes factor (ABF) which is computationally simple and most desirable in genome-wide association studies where hundreds of thousands to a million genetic markers are tested. We treat the approximate Bayes factor as a hybrid Bayes factor which replaces the full data by the maximum likelihood estimates of the parameters of interest in the full model and derive it under a general setting. The deviation from Hardy–Weinberg Equilibrium (HWE) is also taken into account and the ABF for HWE using cases is shown to provide evidence of association between a disease and a genetic marker. Simulation studies and an application are further provided to illustrate the utility of the proposed methodology.     

Implementation of a Federated Search System: Resource Accessibility Issues

Abstract

During 2009, the Hilton M. Briggs Library, South Dakota State University, went live with MetaLib, a federated search engine from Ex Libris. This paper presents the implementation process, addresses resource accessibility issues, and suggests a number of resources that can be consulted about these issues. Readers can apply similar strategies to projects involving federated search systems, as many implementation projects involve the same basic considerations presented here. The author did not find any studies specifically focused on configurations of MetaLib resources, so this content should be singularly useful.     

More on the Preliminary Test Estimator in Almost Unbiased Liu Regression

This article is concerned with the parameter estimation in linear regression model when it is suspected that the regression coefficients are the subspace of the equality restrictions. The objective of this article is to introduce the preliminary test almost unbiased Liu estimators (PTAULE) based on the Wald (W), the likelihood ratio (LR), and the Lagrangian multiplier (LM) tests and compare the proposed estimators in the sense of the quadratic bias and mean square error (MSE) criterion.     

PMSE performance of two different types of preliminary test estimators under a multivariate t error term

Abstract

In this paper, assuming that the error terms follow a multivariate t distribution, we derive the exact formula for the predictive mean squared error (PMSE) of two different types of pretest estimators. It is shown analytically that one of the pretest estimator dominates the SR estimator if a critical value of the pretest is chosen appropriately. Also, we compare the PMSE of the pretest estimators with the MMSE, AMMSE, SR and PSR estimators by numerical evaluations. Our results show that the pretest estimators dominate the OLS estimator for all combinations when the degrees of freedom is not more than 5.