Dynamic factor models

Summary Factor models can cope with many variables without running into scarce degrees of freedom problems often faced in a regression-based analysis. In this article we review recent work on dynamic factor models that have become popular in macroeconomic policy analysis and forecasting. By means of an empirical application we demonstrate that these models turn out to be usefu in investigating macroeconomic problems.     

EXTENDED ANALYSIS FOR RANKED DATA

Standard analyses for ranked data or data which are analyzed using ranks are extended to give better comparisons. The new analysis allows detection of significant quadratic or dispersion effects.     

MORE INFORMATIVE TESTING FOR BIVARIATE SYMMETRY

In testing for bivariate symmetry against arbitrary alternatives the well‐known test developed by Bowker in 1948 is shown to be a score test, and to have useful components. These components are asymptotically independent and asymptotically have the standard normal distribution. Moreover they assess particular pairs of cells for symmetry. These components can also be used in a data analytic manner to complement a test for bivariate symmetry against ordered alternatives.     

对CA6140车床进给系统新的思考

本文在深入分析了ＣＡ６１４０车床进给系统的基础上，提出了用“三轴滑移公用齿轮机构”代替原机床“双轴滑移公用齿轮机构”的总体设想。改进后的机床在进给机构方面不仅能原设计的不足，又能改善其综合功能，获得较好的效果。     

Robust scale estimation in the error-components model using the empirical characteristic function

Robust estimators of the scale parameters in the error-components model are described. The new estimators are based on the empirical characteristic functions of appropriate sets of residuals and are affine equivariant, consistent and asymptotically normal. The robustness of the new estimators is investigated via influence-function calculations. The results of Monte Carlo experiments and an example based on real data illustrate the usefulness of the estimators.     

晋西三川河流域的地表组成物质及其与土壤侵蚀的关系

地表组成物质是影响三川河流域土壤侵蚀及滑坡发育的重要因素。本文在分析该流域的地表组成物质的类型、性质及分布规律的基础上,探讨了地表组成物质与土侵馒蚀的关系。     

QUALITY CONTROL WITH MULTIVARIATE DATA

The paper examines statistical process control of bivariate and multivariate data, using in particular the multivariate equivalents of the univariate Shewhart chart, CUSUM chart and the Exponentially Weighted Moving Average chart. This illustrates the usefulness of Principal Component methods in statistical process control with multivariate data.     

Local principal curves

Principal components are a well established tool in dimension reduction. The extension to principal curves allows for general smooth curves which pass through the middle of a multidimensional data cloud. In this paper local principal curves are introduced, which are based on the localization of principal component analysis. The proposed algorithm is able to identify closed curves as well as multiple curves which may or may not be connected. For the evaluation of the performance of principal curves as tool for data reduction a measure of coverage is suggested. By use of simulated and real data sets the approach is compared to various alternative concepts of principal curves.     

中国农业竞争力国际比较

以中国农业为研究对象,在生产竞争力、技术竞争力、市场竞争力、资本竞争力4个指标的基础上,建立了中国农业国际竞争力评价指标体系。采用主成分分析法,对11个国家2011年农业竞争力的综合排名进行研究。结果显示,我国农业国际竞争力在11个国家中排名第7,农业科研支出、农业总固定资本、种植业固定资产、土地开发和机械设备应用等指标具有明显竞争优势,国际市场竞争力、技术竞争力方面和劳动生产率等指标处于明显的劣势。进而提出提高农业的劳动生产率,重视农产品的市场营销,强化农业科研投入效率等建议。     

Monitoring Nonlinear Profiles with Random Effects by Nonparametric Regression

The monitoring of process/product profiles is presently a growing and promising area of research in statistical process control. This study is aimed at developing monitoring schemes for nonlinear profiles with random effects. We utilize the technique of principal components analysis to analyze the covariance structure of the profiles and propose monitoring schemes based on principal component (PC) scores. The number of the PC scores used in constructing control charts is crucial to the detecting power. In the Phase I analysis of historical data, due to the dependency of the PC-scores, we adopt the usual Hotelling T ² chart to check the stability. For Phase II monitoring, we study individual PC-score control charts, a combined chart scheme that combines all the PC-score charts, and a T ² chart. Although an individual PC-score chart may be perfect for monitoring a particular mode of variation, a chart that can detect general shifts, such as the T ² chart and the combined chart scheme, is more feasible in practice. The performances of the schemes under study are evaluated in terms of the average run length.