Gastrointestinal transit and digestibility of maltitol,sucrose and sorbitol in rats: A multicompartmental model and recovery study

Using data obtained with a dye marker and the gavage technique, the kinetics of gastrointestinal transit of different loads of sugar substitutes (maltitol, sorbitol) and sugar (sucrose) in the rat were analysed using a linear multicompartmental model over a range from the realistic to the non-physiologic high, of carbohydrate intake levels and using only a few experimental time points. The model gave detailed insight into intestinal propulsion and gastrocecal transit time. Rate constants of transport between the compartments investigated were determined; they showed characteristics which could be related to the substance and the dosage administered. Analyses of the gastrointestinal content and calculations of the intestinal net water movement showed that the digestibility and absorption of the disaccharide sugar alcohol, maltitol, in the small gut depended inversely on the dose ingested. For all substances tested, caloric availability in the small intestine was calculated. At a physiological low level of maltitol intake, the results also indicated an insignificant calorie-saving effect in comparison to sucrose, an effect based mainly on the slow absorption rate of the maltitol cleavage product sorbitol.     

Time series forecasting using robust regression

The method of ordinary least squares (OLS) and generalizations of it have been the mainstay of most forecasting methodologies for many years. It is well-known, however, that outliers or unusual values can have a large influence on least-squares estimators. Users of automatic forecasting packages, in particular, need to be aware of the influence that outlying data values can have on statistical analyses and forecasting results. Robust methods are available to modify least-squares procedures so that outliers have much less influence on the final estimates; yet these formal methods have not found their way into general forecasting procedures. This paper provides a case study in which classical least-square-estimation procedures are complemented with a robust alternative to enhance statistical fit criteria and improve forecasting performance. The study suggests that much can be gained in understanding the nature of outliers and their influence on forecasting performance by performing a robust regression in addition to OLS.     

The minimal rank correlation,subject to order restrictions,with application to the weighted linear choice model

The weighted linear choice model is one of the most popular models in the social sciences. In this model the utility of a choice object is represented as a weighted sum of attribute-level desirabilities, where the weights are attribute importances. In many empirical contexts the choice objects are such that individuals are highly correlated in terms of their desirability ordering of levels within attribute (e.g., price levels, durability levels, etc.) but may differ appreciably in terms of their evaluations of each attribute's importance.In this paper we address the problem of how dissimilar two individuals may be, in a rank correlation sense, given that they agree completely on the desirability ordering of levels within attributes, but may disagree considerably regarding the importance they attach to the attributes themselves. The problem has interesting implications regarding the potential value of clustering individuals' utility functions for market segmentation or other such purposes.The authors would like to thank the editor and three anonymous reviewers for their excellent comments on an earlier draft of the paper.     

基于模糊点数据的线性回归分析

在经典回归分析理论中,假定训练数据是独立同分布的随机样本,并且在回归方程的构建中是同等对待的.然而,在许多实际问题中,训练数据的作用是不同的;通常有些训练数据比其它数据可能更为重要,因而不同的训练数据对曲线拟合的贡献应该不同.人们要求重要的训练数据对曲线拟合做出更大的贡献.实现这一目标的策略是给每个训练数据赋予一个置信权重并且重新推导了经典的最小二乘回归方法,分析了它们的统计性质.受文[1]的启发,将这里的样本称为模糊点样本数据.     

多元统计分析在管理中的应用研究

利用正态分布的偏、峰度检验 ,假设检验 ,根据分数所反馈的信息对某班的数学分析课程考试进行了试卷的合理性及试卷的差异的分析研究 ,建立了多元线性回归模型 ,对不同学期分数间的关系进行了统计分析 ,为教学研究和管理提供了科学的依据     

Predicting Stock Return Volatility: Can We Benefit from Regression Models for Return Intervals?

We study the performance of recently developed linear regression models for interval data when it comes to forecasting the uncertainty surrounding future stock returns. These interval data models use easy‐to‐compute daily return intervals during the modeling, estimation and forecasting stage. They have to stand up to comparable point‐data models of the well‐known capital asset pricing model type—which employ single daily returns based on successive closing prices and might allow for GARCH effects—in a comprehensive out‐of‐sample forecasting competition. The latter comprises roughly 1000 daily observations on all 30 stocks that constitute the DAX, Germany's main stock index, for a period covering both the calm market phase before and the more turbulent times during the recent financial crisis. The interval data models clearly outperform simple random walk benchmarks as well as the point‐data competitors in the great majority of cases. This result does not only hold when one‐day‐ahead forecasts of the conditional variance are considered, but is even more evident when the focus is on forecasting the width or the exact location of the next day's return interval. Regression models based on interval arithmetic thus prove to be a promising alternative to established point‐data volatility forecasting tools. Copyright ©2015 John Wiley & Sons, Ltd.     

线性不确定系统约束条件下的控制稳定统一问题

本文讨论了线性不确定系统在控制能量（或控制幅值）受限下的能控性和稳定性的统一问题，证明了判定不确定系统完全能控并且渐近稳定的充分条件，又给出了控制能量（或控制幅值）受限下状态不能控同时也不稳定的一个判据．     

中国股票市场的三因子模型

通过对中国股票市场从1995年7月到2000年6月所有A股股票月收益率的研究，发现股票市场具有显著的市值效应，账面市值比效应、市盈率效应和价格效应，这些效应不能用市场β值来解释，但再加上两个因子：市值因子和账面市值比因子，可以很好地解释这些效应，这个三因子模型也能够很好地解释中国股票市场众多指数的差异。     

基于线性预测滤波的抗速度欺骗干扰技术

针对调频连续波 (FMCW)雷达 ,提出了采用自适应线性预测滤波预处理实现速度欺骗干扰的检测。与直接对回波进行加速度补偿检测法相比 ,只需进行简单的门限检测即可判断干扰的存在及干扰参数估计 ,无需进行复杂的二维检测处理     

基于MATLAB的线性系统极点配置问题的算法分析

线性系统的动态性能主要取决于系统极点的位置。极点配置问题就是把闭环极点组配置到所希望的位置上 ,使综合得到的系统动态性能达到期望的要求。极点配置问题的算法有多种 ,特别是对于多输入系统 ,其计算较为复杂。分析了一个基于龙伯格能控规范型的极点配置问题的算法 ,并针对此算法给出了一个具有实用价值的MATLAB通用程序