Ridge regression estimators in the linear regression models with non-spherical errors

The present paper considers a family of ordinary ridge regression estimators in the linear regression model when the disturbances covariance matrix depends upon a few unknown parameters. An asymptotic expansion for the distribution of the ridge regression estimator is developed and under the quadratic loss function its asymptotic risk is compared with that of the feasible GLS estimator.     

CORRECTING FOR MEASUREMENT ERROR IN AN EXPOSURE-RESPONSE RELATIONSHIP BASED ON DICHOTOMISING A CONTINUOUS DEPENDENT VARIABLE

Random error in a continuous outcome variable does not affect its regression on a predictor. However, when a continuous outcome variable is dichotomised, random measurement error results in a flatter exposure-response relationship with a higher intercept. Although this consequence is similar to the effect of misclassification in a binary outcome variable, it cannot be corrected using techniques appropriate for binary data. Conditional distributions of the measurements of the continuous outcome variable can be corrected if the reliability coefficient of the measurements can be estimated. An unbiased estimate of the exposure-response relationship is then easily calculated. This procedure is demonstrated using data on the relationship between smoking and the development of airway obstruction.     

读《全隋文》札记

清人严可均编纂的《全隋文》,被誉为研究隋代文化的百科全书。但是,由于受历史条件和一人之力的局限,《全隋文》的编纂也存在着严重的缺漏和诸多失误。为了纠正此书所见失误,为研读者提供更为科学之文本,运用内、外证相结合的方法,据以文献、史籍和新出土石刻,共辑得札记23条。其中既有对录文重出互见的厘正、文字讹夺衍倒的校勘,又有文章系年的考订、补充和纠正。需要说明的是,所用《全隋文》为商务印书馆1999版,各则札记先列卷页(商务版卷数用汉字,页码用阿拉伯数字,仍依其旧),次列作者及篇名,再陈鄙见,以便检核。     

人的可靠性与人为差错

分析论述了影响人的可靠性的因素 ,提出了提高人的可靠性、减少人为差错的措施和方法。     

基于支持向量机的传感器非线性误差校正

提出了一种用支持向量机校正传感器非线性误差的原理和方法。该算法只依据样本就可以正确辩识传感器逆模型特征,而不需关于逆模型函数形式的任何先验知识,并将原问题转化为一个凸二次优化问题,能够保证找到的极值解就是全局最优解,具有较好的泛化能力。通过对电容式湿敏传感器误差校正的应用表明:该算法可取得较好的效果。     

维吾尔族大学生在英语写作中中介语语法偏误分析

以中介语理论及其五个发展过程为标准，可将新疆少数民族地区维吾尔族民考民英语学习者在大学英语写作学习中出现的偏误类型分为：母语负迁移型、目标语规则过度归纳型、训练迁移型、交际策略型和二语习得策略型。文章着重探讨了造成前两种中介语语法偏误类型的原因是母语无标记，偏误类推，合成和偏误分析，希望能够引导教师正确认识作文中出现的语言偏误，采用合理的教学设计和方法，帮助三语学习者逐步改进和发展中介语，向目标语靠拢。     

基于中介语错误的可能迁移分析

本研究以华北水利水电学院非英语专业大一学生写作中的错误句子为语料,采用基于定量分析的定性分析方法分析句法迁移在学生特殊过渡时期的表现与作用,从而分析、阐明学生在二语习得中出现错误的内在原因.研究认为句法迁移在二语习得中起着重要的作用,同时普通高校非英语专业一年级大学生在过渡时期遇到不熟练或较复杂的语言输出时,更有可能求助于母语句法结构,他们在过渡时期的英语写作倾向于对母语句法结构的依赖,其二语习得呈规律性.     

ON A MULTIPLE THREE-DECISION PROCEDURE FOR COMPARING SEVERAL TREATMENTS WITH A CONTROL

For the two-sided comparisons of several treatments with a control, a common statistical problem is to decide which treatments are better than the control and which are worse than the control. This paper studies a multiple three-decision procedure for this purpose, proposed by Bohrer (1979) and Bohrer et al. (1981), and provides tables of critical points to facilitate the application of the procedure. The paper defines a power function of the procedure, and tabulates sample sizes necessary to guarantee a given power level. It addresses the problem of optimal sampling allocation in order to maximize the power for a given total sample size, and considers generalization to the situation where the treatments might have unequal numbers of observations.     

Nonparametric density estimation from data with a mixture of Berkson and classical errors

The author considers density estimation from contaminated data where the measurement errors come from two very different sources. A first error, of Berkson type, is incurred before the experiment: the variable X of interest is unobservable and only a surrogate can be measured. A second error, of classical type, is incurred after the experiment: the surrogate can only be observed with measurement error. The author develops two nonparametric estimators of the density of X, valid whenever Berkson, classical or a mixture of both errors are present. Rates of convergence of the estimators are derived and a fully data‐driven procedure is proposed. Finite sample performance is investigated via simulations and on a real data example.     

A Bayesian method of sample size determination with practical applications

Summary.  The problem motivating the paper is the determination of sample size in clinical trials under normal likelihoods and at the substantive testing stage of a financial audit where normality is not an appropriate assumption. A combination of analytical and simulation-based techniques within the Bayesian framework is proposed. The framework accommodates two different prior distributions: one is the general purpose fitting prior distribution that is used in Bayesian analysis and the other is the expert subjective prior distribution, the sampling prior which is believed to generate the parameter values which in turn generate the data. We obtain many theoretical results and one key result is that typical non-informative prior distributions lead to very small sample sizes. In contrast, a very informative prior distribution may either lead to a very small or a very large sample size depending on the location of the centre of the prior distribution and the hypothesized value of the parameter. The methods that are developed are quite general and can be applied to other sample size determination problems. Some numerical illustrations which bring out many other aspects of the optimum sample size are given.