利率期限结构的主成分分析

本文采用主成分分析的方法对我国的利率期限结构进行了研究。在采用这种方法的同时,结合非线性变换BOX—COX得出了我国的利率期限结构具有代表性的三个主成分:利率期限结构曲线的平移、斜率的变化以及曲率的变化。同时通过实证分析证实了这种方法的有效性。     

成分数据主成分分析及其应用

本文分析了传统主成分分析在成分数据分析中的不适应性，介绍了艾奇逊的中心化对数比变换和成分数据主成分分析，并以农民消费结构为例，重点讨论了成分数据主成分分析的实施步骤     

基于非线性主成分神经网络水泥强度预测研究

研究非线性主成分分析法与神经网络算法的融合模型,并将非线性主成分神经网络融合模型应用于水泥强度的预测研究,得到的结果表明预测误差很小,可见研究结果可用于指导水泥生产实践.     

基于非线性变换的PCP-C模型及其在地下水动态分类中的应用

为了克服目前地下水动态分类方法中存在的不能揭示分类指标空间到类型空间的非线性映射关系、方法复杂、计算量大等缺陷,可采用基于非线性变换的主成分投影(PCP)-聚类(C)模型,对地下水动态进行分类.方法首先对分类指标数据进行对数中心化变换,然后应用主成分投影法将变换后的多维指标向量映射到最优一维向量空间,并根据各样本指标在一维向量空间的投影值进行聚类分析,由此得到地下水动态分类结果.地下水动态分类结果表明,建议方法概念清晰,结构简单,计算简便,分类结果可信,是一种有效的地下水动态分类方法.     

基于主成分分析与Fourier变换的动态投资组合

提出了一种将主成分分析与Fourier变换组合的资产投资组合方法.对于N个资产,首先利用主成分分析中第一主成分确定各资产的组合权重并建立投资组合,利用Fourier变换获得该组合残差的复合周期趋势,最后利用ARMA模型对趋势残差进行区间预测.为使资产保值,当组合股价达到最低点时,各资产以第一主成分对应权重进行组合建仓;当组合股价反向上升达到最高点时,则以第N主成分对应权重进行组合并调仓.在实证模拟方面,选取2016年1月4日-2018年6月8日全球股票主要指数的收盘价数据进行实证分析.模拟结果表明:基于主成分分析的投资组合在收益及资产保值方面表现更佳.     

形体老化与疾病的非线性主成分分析

本文把 5个形体老化指标及 13种慢性病指标分别做成两个综合指标 ,再去研究人体老化、疾病与性别及年龄的关系。文中使用非线性主成分法及指出一般线性主成分法的局限性     

基于主成分回归模型的经济增长因素分析

在经济增长因素分析中,常用多元回归分析方法,但有时建立的回归模型拟合效果不好或不合理。为此本文给出建立主成分回归分析的方法。本文对经济增长给出两种回归分析方法,即建立主成分线性回归模型,分析经济增长的边际效应,建立主成分非线性回归模型,分析经济增长的弹性效应,实例表明效果很好。     

我国上市公司财务状况的非线性主成分分析研究

文章通过对我国上市公司的财务指标进行综合分析 ,构建了我国上市公司财务状况综合分析的非线性主成分分析模型 ,并应用该模型对上市公司财务状况进行了合理的评价 .     

核主成分分析(KPCA)在企业经济效益评价中的应用

提出了一种新的经济效益评价模型:核主成分分析(KPCA).它通过一个非线性变换,将原变量空间映射到高维特征空间,然后在高维特征空间中进行线性主成分分析.通过核技巧,只需在原空间进行点积运算,便可使第一主成分的贡献率达到90%以上,能有效避免PCA中因各指标贡献率过于分散而影响评价效果.将该模型应用到广东8个卷烟企业进行评价,得到了较理想的评价效果.     

多元统计分析(Ⅳ)

§4多元数据结构的简化 ──主成分分析和非线性映射 4.1主成分分析方法 多元数据分析上的困难往往是由于数据维数过高.如果有某种方法能把高维空间的数据投影到低维空间,而且这种投影变换又不会使信息损失很多的话,那么就有可能在低维空间上研究这些数据结构了. 例如,三维空间     

数据挖掘技术的理论及应用

数据挖掘是近年来国际上智能信息处理和决策支持分析领域的最前沿的研究方向之一.本文综合介绍了数据挖掘的主要概念和新技术,并展示了其丰富的应用领域.     

交连续dcpo的遗传性和不变性

讨论了交连续dcpo的遗传性和不变性,证明了如下结论:(1)交连续dcpo对于开子空间和闭子空间都是可遗传的;(2)交连续dcpo在加最大元和去最小元运算下保持交连续性;(3)交连续dcpo的收缩核为交连续dcpo.另外,给出了交连续的主理想刻画的一个直接证明;构造了反例说明交连续dcpo对于主滤子是不可遗传的;也构造了反例说明所有主滤子都交连续的一个dcpo,自身不必是交连续的.     

Second-order conditions in stability analysis for state constrained optimal control

The paper presents an outline of the stability results, for state-constrained optimal control problems, recently obtained in Malanowski (Appl. Math. Optim. 55, 255–271, 2007), Malanowski (Optimization, to be published), Malanowski (SIAM J. Optim., to be published). The pricipal novelty of the results is a weakening of the second-order sufficient optimality conditions, under which the solutions and the Lagrange multipliers are locally Lipschitz continuous functions of the parameter. The conditions are weakened by taking into account strongly active state constraints.     

Orderings of coherent systems with randomized dependent components

Consider a general coherent system with independent or dependent components, and assume that the components are randomly chosen from two different stocks, with the components of the first stock having better reliability than the others. Then here we provide sufficient conditions on the component’s lifetimes and on the random numbers of components chosen from the two stocks in order to improve the reliability of the whole system according to different stochastic orders. We also discuss several examples in which such conditions are satisfied and an application to the study of the optimal random allocation of components in series and parallel systems. As a novelty, our study includes the case of coherent systems with dependent components by using basic mathematical tools (and copula theory).     

Scheduling of Products with Common and Product-Dependent Components Manufactured at a Single Facility

This paper analyses a scheduling problem concerned with the production of components at a single manufacturing facility where the manufactured components are subsequently assembled into a finite number of end products. Each product is composed of a common component and a product-dependent component, and completion time of a product is determined by the completion time of the last of two components. All the components are manufactured in a batch process at the single facility and, during the batch process, the manufactured components are individually moved to the next (assembly) station; switching from production of product-dependent components to common components only incurs a set-up cost. The solution properties are characterized subject to the mean flow time measure, based upon which an efficient branch-and-bound solution algorithm is exploited.     

Nonparametric predictive reliability of series of voting systems

Nonparametric Predictive Inference (NPI) for system reliability reflects the dependence of reliabilities of similar components due to limited knowledge from testing. NPI has recently been presented for reliability of a single voting system consisting of multiple types of components. The components are all assumed to play the same role within the system, but with regard to their reliability components of different types are assumed to be independent. The information from tests is available per type of component. This paper presents NPI for systems with subsystems in a series structure, where all subsystems are voting systems and components of the same type can be in different subsystems. As NPI uses only few modelling assumptions, system reliability is quantified by lower and upper probabilities, reflecting the limited information in the test data. The results are illustrated by examples, which also illustrate important aspects of redundancy and diversity for system reliability.     

Joint Reliability Function of Coherent Systems with Shared Heterogeneous Components

In this paper, we consider two coherent systems having shared components. We assume that in the two systems there are three different types of components; components of type one that just belong to the first system, components of type two that lie only in the second system and components of type three that are shared by the two systems. We use the concept of joint survival signature to assess the joint reliability function of the two systems. Using this concept, some representations for the joint reliability function of the system lifetimes are obtained under two different scenarios of component failures. In the first scenario, we assume that the components of the systems fail according to different counting processes such as non-homogeneous Poisson processes. In the second scenario, it is assumed that the component lifetimes of each type are exchangeable while the three types of component lifetimes can be independent or dependent. To illustrate the theoretical results, two systems with shared components are studied numerically and graphically.

     

Optimal use of components of a dyadic wavelet representation

In practice, one may encounter linear transforms whose result is important for a certain set of vector components only. In particular this relates to vector components restored from its dyadic wavelet representation. In this paper we study optimization of the index set of the dyadic wavelet representation which can be used to restore required original vector components.     

Stochastic comparisons of series and parallel systems with randomized independent components

Consider a series or parallel system of independent components and assume that the components are randomly chosen from two different batches, with the components of the first batch being more reliable than those of the second. In this note it is shown that the reliability of the system increases, in usual stochastic order sense, as the random number of components chosen from the first batch increases in increasing convex order. As a consequence, we establish a result analogous to the Parrondo’s paradox, which shows that randomness in the number of components extracted from the two batches improves the reliability of the series system.