Non-nested linear models: A conditional confidence approach

The comparison of nested linear models with normal error is well standardized in the common procedures of the analysis of variance. This article considers the comparison of two non-nested linear models that have the same parameter dimension; the comparison is made on the assumption that the true mean lies somewhere in the linear span of the two models. The analysis leads to a precision-based conditional confidence interval for the unsigned angular direction of the true mean, and this in turn provides a confidence assessment of the two directions that correspond to the two models being compared. The confidence interval is an approximate conditional interval (given the distance of the estimate from the intersection of the hypotheses), and its length as a fraction of π indicates the precision of the confidence procedure. The method provides a conditional-inference alternative to a confidence interval available by Creasy-Fieller analysis.     

线性规划的梯度投影算法

Ｋａｒｍａｒｋａｒ算法是解线性规划的多项式算法，但其具有数值不稳定的缺点，同时，由于它属于内点法，在算法终止时所得的点始终是一个近似最优解。文中给出的梯度投影法，可以穿过区域内部，或穿过区域的边界的相对内部，证明了该方法将在有限步终止。     

Detecting discontinuities in nonparametric regression curves and surfaces

The existence of a discontinuity in a regression function can be inferred by comparing regression estimates based on the data lying on different sides of a point of interest. This idea has been used in earlier research by Hall and Titterington (1992), Müller (1992) and later authors. The use of nonparametric regression allows this to be done without assuming linear or other parametric forms for the continuous part of the underlying regression function. The focus of the present paper is on assessing the evidence for the presence of a discontinuity within a regression function through examination of the standardised differences of ‘left’ and ‘right’ estimators at a variety of covariate values. The calculations for the test are carried out through distributional results on quadratic forms. A graphical method in the form of a reference band to highlight the sources of the evidence for discontinuities is proposed. The methods are also developed for the two covariate case where there are additional issues associated with the presence of a jump location curve. Methods for estimating this curve are also developed. All the techniques, for the one and two covariate situations, are illustrated through applications.     

可变参数动态灰色预测模型的建立与实证研究

在固定参数动态灰色预测模型基础之上进行改进,提出了可变参数动态灰色预测模型.固定参数动态灰色预测模型的参数值为0.5,可变参数动态灰色预测模型的参数值由预测对象的影响因素来决定.根据对我国集成电路产业的应用研究,说明了可变参数动态预测模型具有更好的预测精度.同时,针对可变参数动态灰色预测模型的计算量很大的特点,应用Java编制了应用软件,可以方便快捷地进行运算,有利于该模型的应用推广.     

常系数线性常微分方程及欧拉方程通解的残数表示式

本文应用残数理论建立了 n 阶常系数线性微分方程及欧拉方程通解的另一种表示形式.n 阶非齐次常系数线性微分方程通解的表达式为函数f(z')·e~x/g(z)与F(t)dt/g(z)在极点zj(j=l,2,…l)的残数之和。其中g(x)是z 的n次多项式,在z_j (j=1,2,…l)的值为零,f(z)是任一个解析函数,=1,2,…l)的值不为零.欧拉方程通解有类似结果.     

含有零泛器的线性网络的稀疏表分析法

本文提出了含有零泛器的线性网络的稀疏表分析法（ＳＴＡ），讨论了其算法实现。对比所提出的方法与降阶的节点法的特点后得出结论：本文算法是可行的。     

线性方程组的单调收敛

本文讨论了线性方程组Au=b的单调收敛性,给出了某些线性方程组Au=b占之单调收敛性的判定条件.     

矩阵损失下增长曲线模型中共同均值参数的线性估计的可容许性

在矩阵损失函数下，讨论多元线性模型中共同均值参数的线性估计的可容许性．在几种容许性定义下，参数ＫＨＬ的线性估计ｍｉ＝１ＤｉＹｉＦｉ（ｎｉ＝１ＤｉＹｉＦｉ＋Ｈ）在线性估计类中是可容估计的充要条件被获得     

Bias due to Ignoring the Sample Design in Case–Control Studies

Case–control studies allow efficient estimation of the associations of covariates with a binary response in settings where the probability of a positive response is small. It is well known that covariate–response associations can be consistently estimated using a logistic model by acting as if the case–control (retrospective) data were prospective, and that this result does not hold for other binary regression models. However, in practice an investigator may be interested in fitting a non–logistic link binary regression model and this paper examines the magnitude of the bias resulting from ignoring the case–control sample design with such models. The paper presents an approximation to the magnitude of this bias in terms of the sampling rates of cases and controls, as well as simulation results that show that the bias can be substantial.     

高阶变系数线性微分方程的新算子解法(续)

本文根据变系数线性做分方程的新算子解法，给出某些可积类型．