带移民的碰撞分枝过程的唯一性

本文提出了一种带移民的碰撞分枝过程,它由三部分组成:马氏分枝过程、碰撞分枝过程和状态独立的移民过程,给出了该过程正则性和唯一性判别准则。     

一维扩散过程的最优停止问题的研究

本文研究了一维扩散过程的最优停止问题,论证了W iener过程和几何布朗运动是F e ller过程,同时给出了一般扩散过程的处理方法.     

关于超加过程的遍历极限的识别

该文讨论了随机过程中一类重要过程—超加过程的遍历极限的存在和识别，另外还给出了它们的应用，较完满地解决了超加过程的遍历性．     

带拯救的两参数Markov碰撞过程的遍历性

本文考虑了一类带拯救的两参数Markov碰撞过程.首先讨论了带拯救的两参数Markov碰撞q-矩阵发生函数的性质,通过发生函数给出了过程的正则性和唯一性判别准则,得到了过程的常返性和遍历性的充分必要条件,并给出了几个易于验证的充分条件.最后,给出了遍历情形下该过程平稳分布的发生函数,并给出了过程强遍历的判别准则.     

跳跃扩散过程的期权定价模型

假定股票价格的跳过程为计数过程,建立了股票价格服从跳扩散过程的行为模型.运用随机分析中的鞅方法,推导出了股票价格的跳过程为计数过程的欧式期权定价公式,推广了已有的结果.     

随机过程序列部分和的收敛性

本文讨论了随机过程序列部分和的收敛性问题，给出了部分和过程弱收敛于Gauss过程的条件，得到了随机过程序列场合的嵌入定理及强逼近定理．     

具有马尔可夫骨架的随机过程(英文)

在本文中，我们引入了具有马尔科夫骨架的随机过程的概念．具体讨论了一类重要的具有马氏骨架的随机过程─—（H，Q）─过程，得到了计算这种过程概率分布的向后和向前方程，计算了过程的一维分布以及给出了这种过程正则的充分必要条件．并且本文绘出了文献[3]中主要结果的证明．     

随机环境中的Markov 过程的构造及等价定理

引进了随机转移矩阵, p-m过程和随机环境中的Markov过程等基本概念, 并且给出了一些例子, 特别是给出了由非时齐的密度函数构造随机转移函数的例子. 我们从p-m过程构造了随机环境中的Markov过程和绕积Markov过程, 并且研究了随机环境中的Markov过程、本原过程、环境过程和绕积Markov过程的一些性质. 给出了随机环境中的Markov过程的几个等价定理.     

重尾索赔下的一类相依风险模型的若干问题

本文研究了重尾索赔下的一类相依风险模型,得到了破产概率的尾等价式及索赔盈余过程大偏差的渐近关系式.在该模型中,一索赔到达过程是Poisson过程,另一索赔到达过程为其p-稀疏过程.     

图博弈的过程比例解

本文对具有图结构合作博弈（图博弈）进行了研究，采用比例原则和过程化分配方法，定义了比例分配过程，并对其性质进行了分析。随后，针对比例分配过程的超有效情况，运用等比例妥协的方式给出满足有效性的过程比例解，并研究了稳定性。最后，将比例分配过程与过程比例解应用到破产问题中，得到图博弈过程比例解与破产问题比例规则等价的结论。     

A simulation approach to cost-effectiveness and cost-benefit calculations of screening for the early detection of disease

The computer simulation program Miscan, developed for analysis, prediction and optimization of screening for early detection of disease, has been extended to enable full cost-effectiveness and cost-benefit calculations. The user specifies which of the available cost- and effectiveness-items are to be used and can choose the valuation per unit for each item. The program computes the volume of each item for scenarios with and without screening, and calculates the costs and effectiveness of the simulated screening policy. The program allows for discounting and present value computations, for scale effects, and for quality adjustment of life years for age and disease stage. The use of the program is illustrated with a model of cervical cancer screening that was based on data from the pilot project in the Netherlands. Two screening policies are compared for several discount rates, and for several exchange rates between costs and health effects.     

Sequence of operations analysis for dynamic data structures

This paper introduces a rather general technique for computing the average-case performance of dynamic data structures, subjected to arbitrary sequences of insert, delete, and search operations. The method allows us effectively to evaluate the integrated cost of various interesting data structure implementations, for stacks, dictionaries, symbol tables, priority queues, and linear lists; it can thus be used as a basis for measuring the efficiency of each proposed implementation. For each data type, a specific continued fraction and a family of orthogonal polynomials are associated with sequences of operations: Tchebycheff for stacks, Laguerre for dictionaries, Charlier for symbol tables, Hermite for priority queues, and Meixner for linear lists. Our main result is an explicit expression, for each of the above data types, of the generating function for integrated costs, as a linear integral transform of the generating functions for individual operation costs. We use the result to compute explicitly integrated costs of various implementations of dictionaries and priority queues.     

Multidimensional first and second order symmetric Strang splitting for hyperbolic systems

We propose an algebraic basis for symmetric Strang splitting for first and second order accurate schemes for hyperbolic systems in N dimensions. Examples are given for two and three dimensions. Optimal stability is shown for symmetric systems. Lack of strong stability is shown for a non-symmetric example. Some numerical examples are presented for some Euler-like constant coefficient problems.     

High performance computation for DNS/LES

The paper is focused on high-order compact schemes for direct numerical simulation (DNS) and large eddy simulation (LES) for flow separation, transition, tip vortex, and flow control. A discussion is given for several fundamental issues such as high quality grid generation, high-order schemes for curvilinear coordinates, the CFL condition for complex geometry, and high-order weighted compact schemes for shock capturing and shock–vortex interaction. The computation examples include DNS for K-type and H-type transition, DNS for flow separation and transition around an airfoil with attack angle, control of flow separation by using pulsed jets, and LES simulation for a tip vortex behind the juncture of a wing and flat plate. The computation also shows an almost linear growth in efficiency obtained by using multiple processors.     

‘Strong’-‘weak’ precedence in scheduling: Extensions to series-parallel orders

We examine computational complexity implications for scheduling problems with job precedence relations with respect to strong precedence versus weak precedence. We propose a consistent definition of strong precedence for chains, trees, and series-parallel orders. Using modular decomposition for partially ordered sets (posets), we restate and extend past complexity results for chains and trees as summarized in Dror (1997) [5]. Moreover, for series-parallel posets we establish new computational complexity results for strong precedence constraints for single- and multi-machine problems.     

On the impact of model selection on predictor identification and parameter inference

We assessed the ability of several penalized regression methods for linear and logistic models to identify outcome-associated predictors and the impact of predictor selection on parameter inference for practical sample sizes. We studied effect estimates obtained directly from penalized methods (Algorithm 1), or by refitting selected predictors with standard regression (Algorithm 2). For linear models, penalized linear regression, elastic net, smoothly clipped absolute deviation (SCAD), least angle regression and LASSO had a low false negative (FN) predictor selection rates but false positive (FP) rates above 20 % for all sample and effect sizes. Partial least squares regression had few FPs but many FNs. Only relaxo had low FP and FN rates. For logistic models, LASSO and penalized logistic regression had many FPs and few FNs for all sample and effect sizes. SCAD and adaptive logistic regression had low or moderate FP rates but many FNs. 95 % confidence interval coverage of predictors with null effects was approximately 100 % for Algorithm 1 for all methods, and 95 % for Algorithm 2 for large sample and effect sizes. Coverage was low only for penalized partial least squares (linear regression). For outcome-associated predictors, coverage was close to 95 % for Algorithm 2 for large sample and effect sizes for all methods except penalized partial least squares and penalized logistic regression. Coverage was sub-nominal for Algorithm 1. In conclusion, many methods performed comparably, and while Algorithm 2 is preferred to Algorithm 1 for estimation, it yields valid inference only for large effect and sample sizes.     

Determinants of matrices over semirings

In this paper, the concept of determinants for the matrices over a commutative semiring is introduced, and a development of determinantal identities is presented. This includes a generalization of the Laplace and Binet–Cauchy Theorems, as well as on adjoint matrices. Also, the determinants and the adjoint matrices over a commutative difference-ordered semiring are discussed and some inequalities for the determinants and for the adjoint matrices are obtained. The main results in this paper generalize the corresponding results for matrices over commutative rings, for fuzzy matrices, for lattice matrices and for incline matrices.     

Computing the nonabelian tensor squares of polycyclic groups

In this paper we develop a theory for computing the nonabelian tensor square and related computations for finitely presented groups and specialize it to polycyclic groups. This theory provides a framework for making nonabelian tensor square computations for polycyclic groups and is the basis of an algorithm for computing the nonabelian tensor square for any polycyclic group.     

Stokes方程的压力梯度局部投影间断有限元法

本文对定常的Stokes方程提出了一种新的间断有限元法,通过将通常的间断Galerkin有限元法与压力梯度局部投影相结合,建立了一个稳定的间断有限元格式,对速度和压力的任意分片多项式空间P_l(K),P_m(K)的间断有限元逼近证明了解的存在唯一性,给出了关于速度和压力的L~2范数的最优误差估计.     

Superconvergence of mixed finite element semi-discretizations of two time-dependent problems

We will show that some of the superconvergence properties for the mixed finite element method for elliptic problems are preserved in the mixed semi-discretizations for a diffusion equation and for a Maxwell equation in two space dimensions. With the help of mixed elliptic projection we will present estimates global and pointwise in time. The results for the Maxwell equations form an extension of existing results. For both problems, our results imply that post-processing and a posteriori error estimation for the error in the space discretization can be performed in the same way as for the underlying elliptic problem.