G／G／1排队系统的渐近泊松离去过程

本文给出了Ｇ／Ｇ／１排队系统的离去过程的有限维分布弱收敛到泊松过程的有限维分布的条件,特别给出了生灭排队系统及Ｇ／Ｍ／１排队系统的离去过程的有限维分布弱收敛到泊松过程的有限维分布的简单条件．     

以分数布朗运动为输入过程的存储过程生成的上穿点过程

本文研究了以分数布朗运动为输入过程的存储过程上穿高水平u形成的点过程的渐近泊松特性,结果表明当分数布朗运动参数H∈(0,1/2),u→∞时,该点过程弱收敛到泊松过程.     

M/G/1工作休假和休假中止排队

本文分析了一个泊松到达、一般服务的单服务台休假排队，休假策略是工作休假和休假中止．通过嵌入马氏链的方法给出了系统稳态条件，并通过补充变量的方法给出了系统稳态队长的概率母函数。关键词：M／G／1排队系统；工作休假和休假中止；嵌入马氏链；补充变量法     

二维带跳Navier-Stokes方程解的大偏差原理

在带泊松跳二维随机Navier-Stokes方程解的解的存在唯一性的基础上,利用弱收敛的方法证明了带泊松跳二维随机Navier-Stokes方程解的Freidlin-Wentzell型的大偏差原理.     

基于经验似然方法的向量复合泊松过程研究（英文）

在本文中,在随机过程的一阶矩和二阶矩都存在的条件下,当随机过程时间趋于无穷大时,我们将证明关于向量复合泊松过程期望的对数似然比统计量依分布收敛到F分布.最后,通过数值模拟实验表明我们的方法是可行的.     

一类马氏调节反射跳扩散过程的平稳性（英文）

本文拓展文献[1]的马氏调节反射布朗运动模型到马氏调节反射跳-扩散过程,其中跳元素被表述为一个马氏调节复合泊松过程.我们主要计算有关该马氏调节反射跳-扩散过程的平稳分布.我们用一个具有两状态例子通过合适的边界条件来说明如何求解平稳分布所满足的积分-微分方程组.最后,作为一个特殊情况,我们给出无马氏调节反射-扩散过程的平稳分布.     

以分数布朗运动为输入过程的存储过程生成的上穿点过程（英文）

本文研究了以分数布朗运动为输入过程的存储过程上穿高水平u形成的点过程的渐近泊松特性,结果表明当分数布朗运动参数H∈(0,1/2),u→∞时,该点过程弱收敛到泊松过程.     

GI／G／1排队系统的队长和等待时间的瞬时分布

本是[1，2]的继续,在本中利用马氏骨架过程给出了GI／G／1排队系统的队长的瞬时分布的另一新的计算方法和等待时间的计算方法。     

多状态马氏链的极限定理

本文首先对具有平稳转移概率的有限状态整值马氏链［Ｘｉ］的和Ｓｎ给出了它的概率母函数的一般表达式。利用这一结果，对于二状态马氏链，在很一般的条件下证明了Ｓｎ的分布收敛于几何型分布和复合泊松分布的卷积，较强意义下的收敛性也是被讨论的，对于多状态链，某些特殊情形的极限分布是被给出的。     

可数马氏链的截断扩充逼近算法

本文是一篇关于可数马氏链截断扩充逼近算法的综述性文章.截断扩充逼近算法是研究可数无限马氏链的一个有效的方法.它已经成为计算马氏链的平稳分布以及其他参数的关键性工具.本文首先应用截断扩充逼近算法对平稳分布进行研究.我们利用遍历方法以及扰动方法,分别给出在全变差范数意义下以及在V范数意义下的平稳分布的收敛性和误差界.其次,本文应用截断扩充逼近算法研究泊松方程的解.我们给出泊松方程的解的收敛性质,并且考虑中心极限定理中偏差常数的逼近算法.此外,我们将用一些实际的例子来验证这些结果的实用性与准确性.最后,本文对截断扩充逼近算法的一些延伸问题进行了总结与展望.     

Heavy traffic limit theorems for a queue with Poisson ON/OFF long-range dependent sources and general service time distribution

In Internet environment, traffic flow to a link is typically modeled by superposition of ON/OFF based sources. During each ON-period for a particular source, packets arrive according to a Poisson process and packet sizes (hence service times) can be generally distributed. In this paper, we establish heavy traffic limit theorems to provide suitable approximations for the system under first-in first-out (FIFO) and work-conserving service discipline, which state that, when the lengths of both ON- and OFF-periods are lightly tailed, the sequences of the scaled queue length and workload processes converge weakly to short-range dependent reflecting Gaussian processes, and when the lengths of ON- and/or OFF-periods are heavily tailed with infinite variance, the sequences converge weakly to either reflecting fractional Brownian motions (FBMs) or certain type of longrange dependent reflecting Gaussian processes depending on the choice of scaling as the number of superposed sources tends to infinity. Moreover, the sequences exhibit a state space collapse-like property when the number of sources is large enough, which is a kind of extension of the well-known Little??s law for M/M/1 queueing system. Theory to justify the approximations is based on appropriate heavy traffic conditions which essentially mean that the service rate closely approaches the arrival rate when the number of input sources tends to infinity.     

Approximation of optimal stopping problems

We consider optimal stopping of independent sequences. Assuming that the corresponding imbedded planar point processes converge to a Poisson process we introduce some additional conditions which allow to approximate the optimal stopping problem of the discrete time sequence by the optimal stopping of the limiting Poisson process. The optimal stopping of the involved Poisson processes is reduced to a differential equation for the critical curve which can be solved in several examples. We apply this method to obtain approximations for the stopping of iid sequences in the domain of max-stable laws with observation costs and with discount factors.     

On the fluid limit of the M/G/∞ queue

The paper deals with the fluid limits of some generalized M/G/∞ queues under heavy-traffic scaling. The target application is the modeling of Internet traffic at the flow level. Our paper first gives a simplified approach in the case of Poisson arrivals. Expressing the state process as a functional of some Poisson point process, an elementary proof for limit theorems based on martingales techniques and weak convergence results is given. The paper illustrates in the special Poisson arrivals case the classical heavy-traffic limit theorems for the G/G/∞ queue developed earlier by Borovkov and by Iglehart, and later by Krichagina and Puhalskii. In addition, asymptotics for the covariance of the limit Gaussian processes are obtained for some classes of service time distributions, which are useful to derive in practice the key parameters of these distributions.     

On stochastic models of teletraffic with heavy-tailed distributions

Following the approach suggested by I. Kaj and M. Taqqu, we consider a stochastic model of teletraffic based on Poisson random measure. We show that under appropriate assumptions, the finite-dimensional distributions for the scaled workload process converge to those of a stable Lévy process. Bibliography: 10 titles.     

A network of priority queues in heavy traffic: One bottleneck station

In this paper we consider an open queueing network having multiple classes, priorities, and general service time distributions. In the case where there is a single bottleneck station we conjecture that normalized queue length and sojourn time processes converge, in the heavy traffic limit, to one-dimensional reflected Brownian motion, and present expressions for its drift and variance. The conjecture is motivated by known heavy traffic limit theorems for some special cases of the general model, and some conjectured “Heavy Traffic Principles” derived from them. Using the known stationary distribution of one-dimensional reflected Brownian motion, we present expressions for the heavy traffic limit of stationary queue length and sojourn time distributions and moments. For systems with Markov routing we are able to explicitly calculate the limits.     

Characterization of Classical and Quantum Poisson Systems by Thinnings and Splittings

There exist several well–known characterizations of Poisson and mixed Poisson point processes (Cox processes) by thinning and splitting procedures. So a point process is necessarily a Cox process if for arbitrary small thinning parameter it can be obtained by a thinning of some other point process [30]. Poisson processes are characterized by the independence of the two random subconfigurations obtained by an independent splitting of the configuration into two parts [11]. For quantum mechanical particle systems beam splittings which are well–known in quantum optics provide analogous procedures. It is shown that coherent states respectively mixtures of them can be characterized in the same way as Poisson processes and Cox processes. Moreover, for the position distributions of these states which are “classical” point processes just the above mentioned characterizations are obtained. As example of mixed coherent states we consider Gaussian states which arise as equilibrium states of ideal Bose gases.     

Strong convergence of distributions of functionals of a sequence of processes,linearly generated by independent random variables

In the present paper we get sufficient conditions for the strong convergence of distributions of functionals of a sequence of stochastic processes, linearly generated by independent random variables, in the case when the distributions of these processes converge weakly to a Gaussian measure.Translated from Zapiski Nauchnykh Seminarov Leningradskogo Otdeleniya Matematicheskogo Instituta im. V. A. Steklova AN SSSR, Vol. 158, pp. 122–126, 1987.     

Extreme and high-level sojourns of the single server queue in heavy traffic

This study characterizes the behavior of large queue lengths in heavy traffic. We show that the distribution of the maximum queue length in a random time interval for a queueing systems in heavy traffic converges to a novel extreme value distribution. We also study the processes that record the times that the queue length exceeds a high level and the cumulative time the queue is above the level. We show that these processes converge in distribution to compound Poisson processes. This revised version was published online in June 2006 with corrections to the Cover Date.     

Jump diffusion processes and their applications in insurance and finance

For insurance risks, jump processes such as homogeneous/non-homogeneous compound Poisson processes and compound Cox processes have been used to model aggregate losses. If we consider the economic assumption of a positive interest to aggregate losses, Lévy processes have proven to be useful. Also in financial modelling, it has been observed that diffusion models are not robust enough to capture the appearance of jumps in underlying asset prices and interest rates. As a result, jump diffusion processes, which are, simply speaking, combinations of compound Poisson processes with Brownian motion, have gained popularity for modelling in insurance and finance. In this paper, considering a jump diffusion process, we obtain the explicit expression of the joint Laplace transform of the distribution of a jump diffusion process and its integrated process, assuming that jump size follows the mixture of two exponential distributions, which is a special case of phase-type distributions. Based on this Laplace transform, we derive the moments of the aggregate accumulated claim amounts of insurance risk. For a financial application, we concern non-defaultable zero-coupon bond pricing. We also provide several numerical examples for the moments of aggregate accumulated claims and default-free zero-coupon bond prices.