威布尔分市场合无失效数据的可靠性分析

拿文综合了近几年来对威布尔分布和指数分布的无失效数据处理的几种方法这些方法是经典方法、贝叶斯方法、最小x~2方法、等效失效敷方法,并对这些方法作了适当的分析,提出进一步需研究的问题。     

几类改进的新的两步六阶Chebyshev-Halley方法

利用权函数法,给出非线性方程求根的Chebyshev-Halley方法的几类改进方法,证明方法六阶收敛到单根.Chebyshev-Halley方法的效率指数为1.442,改进后的两步方法的效率指数为1.565.最后给出数值试验,且与牛顿法,Chebyshev-Halley 方法及其它已知的方程求根方法做了比较.结果表明方法具有一定的优越性.     

传统隐式Runge-Kutta方法的转换方法

多级隐式Runge-Kutta(RK)方法簇中,除Gauss类方法是s级2s阶的辛方法以外,Radau类方法和Lobatto类方法既不是s级2s阶的方法也不是辛方法.基于隐式RK方法是一类转换RK方法这一特征,利用V-变换和Pade对角逼近,提出了构造高阶RK方法的转换定理.依据转换定理,导出了s级2s阶的Radau方法和s级2s阶的Lobatto方法.利用V-变换和待定系数法,导出了辛Radau方法和辛Lobatto方法.在此基础上,发现并证明了辛Radau方法是s级2s阶的方法.     

一类新的求解非线性方程的七阶方法

利用权函数法给出了一类求解非线性方程单根的七阶收敛的方法.每步迭代需要计算三个函数值和一个导数值,因此方法的效率指数为1.627.数值试验给出了该方法与牛顿法及同类方法的比较,显示了该方法的优越性.最后指出Kou等人给出的七阶方法是方法的特例.     

求解非线性方程重根的平方收敛迭代法

研究了具有重根的非线性方程的迭代方法,对基于动力系统的新牛顿类方法作了修改,改进方法仍保持了牛顿方法的二阶收敛性.数值实验结果验证了方法的有效性.     

解线性互补问题的预处理加速模Gauss-Seidel迭代方法

本文提出了解线性互补问题的预处理加速模系Gauss-Seidel迭代方法,当线性互补问题的系统矩阵是M-矩阵时证明了方法的收敛性,并给出了该预处理方法关于原方法的一个比较定理.数值实验显示该预处理迭代方法明显加速了原方法的收敛.     

Copula理论在信用风险研究中的应用

信用风险研究足近些年来金融数学中的一个崭新的研究方向.本文主要研究了组合信用风险中的常用方法:违约相关性的Copula方法.本文建立了Copula方法与违约相关性研究中的结构化方法和约化方法的联系.此外对于单个公司的生存概率的研究,本文给出了不同于Lando (1998)的求解和证明方法,而这种方法不需要在现在就知道将...     

改进的基于特征向量集的距离判别及在企业信用评价中的应用

在基于特征向量集的距离判别的基础上,提出新的判别分析方法,试图解决现有判别分析方法中计算量大及对复杂数据判别效果差的缺点.同时,将方法用于企业信用评价中,并与传统的判别方法及一些改进的判别方法作比较,实验结果表明,方法提高了企业信用评价的准确率.     

自适应多重网格法与超松弛法的比较

多重网格法(Multiple Grid Method,简称M-G方法)是近年来出现的快速方法之一,本文在M-G方法中采用自适应控制层间转换的技术,并将自适应M-G方法与G-S迭代方法及SOR迭代方,法进行了比较。其计算结果表明,自适应M-G方法的计算量比G-S迭代及SOR迭代少得多,当M-G方法所用层数为4-6层,这种优越性就更加明显,且自适应M-G方法中选取控制参数有很大的灵活性。     

随机波动率模型下奇异期权定价的Monte Carlo方法

Monte Carlo方法是期权定价的经典方法之一,但是收敛速度较慢.针对Hull-White随机波动率模型提出一个拟Monte Carlo方法(QMC)与对偶变量法(AV)相结合的QMCAV方法,利用该方法可以处理一些奇异期权的定价问题.应用Monte Carlo方法(MC),拟Monte Carlo方法,对偶变量法和QMCAV方法分别进行数值模拟计算,给出了在不同参数变化下回望期权与亚式期权的模拟定价.数值实验表明,QMCAV方法较MC,QMC,AV方法更加稳定有效.     

Optimization of Approximate Solution of Integral Equations of Several Variables

In this paper, we consider the problem of optimization of adaptive direct methods of operator equations. Adaptivity of a direct method is understood in the sense that the subspace on the basis of which it is constructed is chosen depending on the operator of the concrete equation (otherwise, nonadaptive direct method is then concerned), which would essentially let us increase the precision. For some classes of the second kind of Fredhlom integral equations with anisotropic smooth kernels we determine the exact order of the error of adaptive direct methods, and we also give an optimal algorithm. Received April 13, 2001, Accepted September 13, 2001     

多元Fredholm积分方程自适应直接方法的优化

考虑了以各向异性光滑函数为核及自由项的多元Fredholm积分方程类的自适应直接方法的优化,得到误差阶的精确估计及相应的最优算法。     

多元积分方程自适应解法的优化

给出了核属于Besov空间的第二类Fredholm积分方程自适应的最优算法,并得到相关的误差阶的精确估计。     

Optimization of adaptive direct algorithms for approximate solution of integral equation

The concern of this paper is to study the optimization of adaptive direct algorithms for approximate solution of the second kind Fredholm integral equations. We derive the exact order of the problem with integral kernels belonging to the Besov classes. Furthermore, we also present an almost optimal adaptive direct algorithm for above equation class.     

核属于H函数类的多维积分方程近似解直接方法的优化

本文我们确定了核属于 H函数类的多维第二类 Fredholm积分方程类在自适直接方法意义下的最优近似解的精确阶估计 ,并给出了最优算法 .     

OPTIMIZATION OF ADAPTIVE DIRECT METHOD FOR APPROXIMATE SOLUTION OF INTEGRAL EQUATIONS OF SEVERAL VARIABLES

This paper determines the exact error order on optimization of adaptive directmethods of approximate solution of the class of Fredholm integral equations of the secondkind with kernel belonging to the anisotropic Sobolev classes, and also gives an optimalalgorithm.     

Optimization of adaptive direct methods for the solution of operator equations in Hilbert space

Some general theorems on estimates of error of optimal adaptive direct methods of solution of operator equations of type II in Hilbert space are obtained.Translated from Ukrainskii Matematicheskii Zhurnal, Vol. 42, No. 1, pp. 95–102, January, 1990.     

On direct methods for solution of regularized equations

We prove that the application of so-called adaptive direct methods to approximation of Fredholm equations of the first kind leads to a more economical way of finite-dimensional approximation as compared with traditional approaches.Translated from Ukrainskii Matematicheskii Zhurnal, Vol. 47, No. 9, pp. 1231–1242, September, 1995.     

An efficient algorithm for the parallel solution of high-dimensional differential equations

The study of high-dimensional differential equations is challenging and difficult due to the analytical and computational intractability. Here, we improve the speed of waveform relaxation (WR), a method to simulate high-dimensional differential-algebraic equations. This new method termed adaptive waveform relaxation (AWR) is tested on a communication network example. Further, we propose different heuristics for computing graph partitions tailored to adaptive waveform relaxation. We find that AWR coupled with appropriate graph partitioning methods provides a speedup by a factor between 3 and 16.     

多元积分方程自适应解法的最优化

In this paper it was considered that problem of optimization of adaptive direct algorithm of approximate solution of integral equations. For the Fredholm integral equations of second kind with kernels belonging to Besov classes there is determined the exact order of the error of an optimal adaptive direct algorithm and a algorithm for realizing it is indicated.