半相依回归系统参数的Stein型主成分改进估计

将S tein压缩思想与主成分改进估计相结合,研究两个半相依回归系统.当设计阵呈病态时,提出S tein型主成分改进估计,同时,给出当V未知时的两步估计.证明在均方误差意义下,S tein型主成分改进估计局部优于主成分改进估计和协方差改进估计.     

曲线的主法线曲面

在三维欧氏空间中,作为特殊曲线,Mannheim曲线、Bertrand曲线以及一般螺线具有良好的几何和代数性质.讨论了三维欧氏空间中特殊曲线的主法线曲面.根据渐近曲线的方程,具体给出主法线曲面的一族非直线的渐近曲线.再根据平均曲率、高斯曲率及主曲率函数,能得到曲线的主法线曲面的极小轨迹、常高斯曲率曲线及两个主曲率函数之比为常数的曲线.还给出曲面上测地线和腰曲线的性质.     

基于董事会治理因素的财务危机预警模型的构建

企业在经营过程中存在着越来越多的财务风险,为了防止这些风险演变为财务危机,及时进行财务危机预警分析,就需要理顺公司的治理结构,引入董事会治理因素来完善财务危机预警机制.以120家上市公司为研究对象,分别运用非参数检验、T检验以及主成分分析对财务变量和董事会治理变量进行筛选,进而运用Logistic回归分析构建预警模型.结果显示,未引入董事会治理变量的模型的预测正确率为92.5%,而引入董事会治理变量的模型预测正确率为94.15%,预警能力明显增强,也说明,董事会治理因素是影响公司财务危机的一个重要方面.     

基于核函数主元分析的SVM建模方法及应用

为有效克服线性建模方法在非线性建模方面的不足,将核函数思想引入到主元分析方法(PCA)中,有效提取实验数据中的非线性特征信息,并将其作为支持向量机(SVM)的输入变量,建立工业过程软测量模型。该方法应用于丙烯腈聚合过程中转化率的预报,结果表明:该方法的预测精度优于PCA-SVM方法和KPCA-NN方法。     

智能控制电采暖系统的应用

对当前常用的几种采暖方式进行了分析比较,重点对节能智能控制电采暖系统的工作原理、技术特点、应用前景予以阐述.     

Does a lot help a lot? Forecasting stock returns with pooling strategies in a data‐rich environment

A variety of recent studies provide a skeptical view on the predictability of stock returns. Empirical evidence shows that most prediction models suffer from a loss of information, model uncertainty, and structural instability by relying on low‐dimensional information sets. In this study, we evaluate the predictive ability of various lately refined forecasting strategies, which handle these issues by incorporating information from many potential predictor variables simultaneously. We investigate whether forecasting strategies that (i) combine information and (ii) combine individual forecasts are useful to predict US stock returns, that is, the market excess return, size, value, and the momentum premium. Our results show that methods combining information have remarkable in‐sample predictive ability. However, the out‐of‐sample performance suffers from highly volatile forecast errors. Forecast combinations face a better bias–efficiency trade‐off, yielding a consistently superior forecast performance for the market excess return and the size premium even after the 1970s.     

考虑经纪人投资情绪的委托代理合同研究

从行为金融学角度,提出将经纪人的投资情绪考虑进资本市场的委托代理关系中.通过建立数学模型,分析了非理性经纪人的投资决策给委托人带来的影响,得到了此时委托人与经纪人之间的最优委托代理合同.结果表明,经纪人的乐(悲)观投资情绪可以使委托人的代理成本得到补偿,并且委托人对经纪人的最优激励强度随着经纪人乐(悲)观程度的增加而降低.这说明在一定条件下,经纪人的乐(悲)观投资情绪,对委托人具有积极意义.     

海滨锦葵优良单系杂交F2代产量性状的广义遗传力及其主成分分析

以海滨锦葵优良单系杂交的F2代群体为材料,对产量性状进行了广义遗传力、相关性和主成分分析,以期为提高海滨锦葵产量提供有益信息.结果表明:F2家系单株种子产量平均值为12.84 g,比2001年在滩涂海滨锦葵自然生长群体中随机选择的80个单系的平均单株产量(4.25 g/单系)有显著提高;在10个产量性状中,广义遗传力较高的依次是结果枝比、种子成熟度、结果枝数、分枝数和果实数;6个因子(果实数、地径、结果枝数、株高、分枝数和结果枝比)与单株产量高度正相关,且这6个因子彼此高度相关;结果枝高度与上述6个因子及产量均呈显著负相关.主成分分析表明,影响单株产量的依次是结果枝数、地径、分枝数、株高和果实数.对海滨锦葵而言,地径和分枝数的增加是获得高产的关键,而结果枝高度的负选择也可显著提高种子产量.     

基于主成分回归分析的瓦斯含量预测

为了增加多元回归模型预测的精度,将主成分分析与多元回归分析相结合提出了PCA—MRA模型,并将该模型用于实际瓦斯含量预测。结果表明,PCA—MRA模型消除了输入变量之间的相关性,减少了输入变量值个数,提高了预测精度,便于实际推广和应用,为瓦斯含量预测提供一种新的途径。     

Forecasting Death Rates Using Exogenous Determinants

Mortality models used for forecasting are predominantly based on the statistical properties of time series and do not generally incorporate an understanding of the forces driving secular trends. This paper addresses three research questions: Can the factors found in stochastic mortality‐forecasting models be associated with real‐world trends in health‐related variables? Does inclusion of health‐related factors in models improve forecasts? Do resulting models give better forecasts than existing stochastic mortality models? We consider whether the space spanned by the latent factor structure in mortality data can be adequately described by developments in gross domestic product, health expenditure and lifestyle‐related risk factors using statistical techniques developed in macroeconomics and finance. These covariates are then shown to improve forecasts when incorporated into a Bayesian hierarchical model. Results are comparable or better than benchmark stochastic mortality models. Copyright © 2014 John Wiley & Sons, Ltd.