西安杨官寨遗址是中华文明首源象征地——中国聚落考古“三山一水”初步比较

在公认“中华文明多源论”的前提下,“三山”（华山、龙山与红山）被不同考古学家视为中华文明首源象征地。作为仰韶文化（华山）中的佼佼者,距今6000～5000年前的西安杨官寨遗址虽然目前还未全部发掘完毕,但从各方面看,包括其地出土陶祖,足以确证其即中华文明首源象征地。而与其同时的红山辽西牛河梁遗址体现的则是落后于西安杨官寨遗址的女权文化。郭大顺教授的“主要实证”及“一人独尊”说等均难成立。至于龙山文化虽然出场时浓妆惊艳,但是毕竟珊珊来迟,不足以构成对西安杨官寨遗址作为中国文明首源象征地的挑战。综合比较“三山”。显然西安杨官寨遗址堪作中国文明首源象征地。     

Average run length comparison of multivariate control charts

In this paper we use Monte Carlo Simulation methodology to compare the effectiveness of five multivariate quality control methods, namely Hotelling T ², Multivariate Shewhart Char, Discriminant Analysis, Decomposition Method, and Multivariate Ridge Residual Chart-developed by Authors-, for controlling the mean vector in a multivariate process. P-dimensional multivariate normal data generated using different covariance structures. Various amount of shift in the mean vector is induced and the resulting Average Run Length (ARL) is computed. The effectiveness of each method with regard to ARL is discussed.     

Efficiency of two classes of stochastic restricted almost unbiased type principal component estimators in linear regression model

In this paper, we introduce two new classes of estimators called the stochastic restricted almost unbiased ridge-type principal component estimator (SRAURPCE) and the stochastic restricted almost unbiased Liu-type principal component estimator (SRAURPCE) to overcome the well-known multicollinearity problem in linear regression model. For the two cases when the restrictions are true and not true, necessary and sufficient conditions for the superiority of the proposed estimators are derived and compared, respectively. Furthermore, a Monte Carlo simulation study and a numerical example are given to illustrate the performance of the proposed estimators.     

"数据库原理及应用"课程教学改革初探

文章分析了机电专业数据库原理及应用课程教学的现状,结合该课程特点,从教学内容、教学手段、考核方式等方面探索了该课程的教学改革.     

A jackknifed difference-based ridge estimator in the partial linear model with correlated errors

Tabakan and Akdeniz [Difference-based ridge estimator of parameters in partial linear model. Statist Pap. 2010;51(2):357–368] proposed a difference-based ridge estimator (DBRE) in the partial linear model. In this paper, a new estimator is introduced by jackknifing the DBRE that Tabakan and Akdeniz presented. We investigate the performance of this new estimator over the DBRE and difference-based estimator introduced by Yatchew [An elementary estimator of the partial linear model. Econom Lett. 1997;57:135–143] in terms of mean-squared error and mean-squared error matrix and a numerical example is provided to demonstrate the performance of the estimators.     

安徽省产业结构与农村劳动力转移关系的实证研究

农村劳动力转移一直在安徽省长期存在,这种现象出现的原因很多,既有国家政策的影响,也有区域经济发展不平衡的问题,更有个人因素等.而产业结构对农村劳动力转移也起着很大的作用,尤其是构成产业结构中的相关指标如第一产业、第二产业、建筑业、第三产业总值、农用机械总动力、城镇化水平和城乡居民人均收入比等因素影响明显,这些因素中除第一产业外,其他因素都对农村劳动力转移起到正面的影响,因而大力发展现代农业、城镇工业、建筑业、特别是第三产业能够促使安徽省农村劳动力实现更加合理化的转移.     

Multivariate Calibration — Direct and Indirect Regression Methodology

This paper tries first to introduce and motivate the methodology of multivariate calibration. Next a review is given, mostly avoiding technicalities, of the somewhat messy theory of the subject. Two approaches are distinguished: the estimation approach (controlled calibration) and the prediction approach (natural calibration). Among problems discussed are the choice of estimator, the choice of confidence region, methodology for handling situations with more variables than observations, near-collinearities (with counter-measures like ridge type regression, principal components regression, partial least squares regression and continuum regression), pretreatment of data, and cross-validation vs true prediction. Examples discussed in detail concern estimation of the age of a rhinoceros from its horn lengths (low-dimensional), and nitrate prediction in waste-water from high-dimensional spectroscopic measurements.     

Smoothing in an underdetermined linear model with random explanatory variables

In some physical systems, where the goal is to describe behaviour over an entire field using scattered observations, a multiple regression model can be derived from the discretization of a continuous process. These models often have more parameters than observations. We propose a technique for constructing smoothed estimators in this situation. Our method assumes the model has random explanatory and response variables, and imposes a smoothness penalty based on the signal-to-noise ratio of the model. Results are présentés using a known value for the ratio, and a method for estimating the ratio is discussed. The procedure is applied to modelling temperature measurements taken in the California Current.