A Semi-parametric Regression Model with Errors in Variables

Abstract.  In this paper, we consider a partial linear regression model with measurement errors in possibly all the variables. We use a method of moments and deconvolution to construct a new class of parametric estimators together with a non-parametric kernel estimator. Strong convergence, optimal rate of weak convergence and asymptotic normality of the estimators are investigated.     

约束优化问题的异步并行拟牛顿方法

提出了一种求解等式约束优化问题的异步并行拟牛顿方法 .若假设目标函数 f和约束函数h至少三次连续可微 ,且△h(x)对任意x∈Rn 均为满秩矩阵 ,证明了所提出的异步并行算法是 q—超线性收敛的 .     

Adaptive tests of regression functions via multiscale generalized likelihood ratios

Many applications of nonparametric tests based on curve estimation involve selecting a smoothing parameter. The author proposes an adaptive test that combines several generalized likelihood ratio tests in order to get power performance nearly equal to whichever of the component tests is best. She derives the asymptotic joint distribution of the component tests and that of the proposed test under the null hypothesis. She also develops a simple method of selecting the smoothing parameters for the proposed test and presents two approximate methods for obtaining its P‐value. Finally, she evaluates the proposed test through simulations and illustrates its application to a set of real data.     

关于函数列收敛与一致收敛的一点思考

通过定义、定理、正反对比的例题论述了函数列收敛、一致收敛、内闭一致收敛及其之间的关系与差异。     

Deconvolution with supersmooth distributions

Nonparametric deconvolution problems require one to recover an unknown density when the data are contaminated with errors. Optimal global rates of convergence are found under the weighted L_p-loss (1 ≤ p ≤ ∞). It appears that the optimal rates of convergence are extremely low for supersmooth error distributions. To resolve this difficulty, we examine how high the noise level can be for deconvolution to be feasible, and for the deconvolution estimate to be as good as the ordinary density estimate. It is shown that if the noise level is not too high, nonparametric Gaussian deconvolution can still be practical. Several simulation studies are also presented.     

TESTING SPHERICITY UNDER A MIXTURE MODEL

The robustness of Mauchly's sphericity test criterion when sampling from a mixture of two multivariate normal distributions is studied. The distribution of the sphericity test criterion when the sample covariance matrix has a non-central Wishart density of rank one is derived in terms of Meijer's G-functions; its distribution under the mixture model is then deduced. The robustness is studied by computing actual significance levels of the test under the mixture model using the critical values under the usual normal model.     

南瓜营养液的生产技术

介绍了南瓜营养液的生产工艺和动物实验效果。     

关于线性互补问题的迭代算法

建立了一类求解线性互补问题的迭代算法。在一定条件下,研究了保证原问题的解存在唯一的充分条件,并且证明了新算法的收敛性。     

论大学英语水平统一测试的优越性

我国现行有两套考试系统用以测试大学英语水平:大学英语46、级考试(CET-4/6)用来衡量非英语专业学生的英语水平,而英语专业48、级(TEM-4/8)考试则用来测评英语专业学生的英语水平。依据Bachman和Palmer语言测试原则,为了保证语言测试的有效性,语言测试任务应该与语言应用任务相对应,这种对应是语言测试的出发点和目的。既然如此,对于非母语的中国大学生而言,就没有必要以英语专业或非英语专业的区分用不同的测试来区分他们的英语水平。从这一点出发,完全可以将现行测试非英语专业学生CET-4/6和测试英语专业学生的TEM-4/8合二为一。问卷调查分析也表明,实行全国大学英语统一测试比分成两套考试系统的英语测试更具优越性。     

The Robustness of Trend Stationarity: An Illustration with the Extended Nelson-Plosser Dataset

We re-evaluate Andreu and Spanos's findings in favour of trend stationarity by considering the extended Nelson-Plosser data set. This expanded (to 1988) data set includes a period of rather different behaviour compared with the original Nelson-Plosser data used by Andreou and Spanos. We find that Andreou and Spanos's models (with only minor adjustments) exhibit remarable stability over this extended period, and indicate that their conclusions are more robust than they have shown.