复合泊松过程的可加性

对复合泊松分布可加性的研究在许多的文献中都可以看到,本文首先应用特征函数的方法证明了复合泊松分布的可加性.以此为基础,结合对随机过程相关性质的讨论,证明了复合泊松过程也具有与复合泊松分布可加性相似的,某种意义上的可加性性质.     

截尾平稳泊松过程及泊松流的分布

本文分析了区间〔０，＋∞〕上强度为λ（常数）的泊松过程的性质，提出了另一类新的模型－－截尾平稳泊松过程，得出了截尾平稳泊松过程的性质及泊松流的分布。     

泊松过程与时间变换

本文通过讨论时间齐次泊松过程和时间非齐次泊松过程之间的联系,指出在时间变换意义下,二者事实上是等价的.借此希望帮助本科学生加深对泊松过程的理解,启发学生对深一层次问题的思考.     

直观实用的泊松图

本文介绍一种用来诊断数据是否来自泊松总体的方法—泊松图，并通过实例分析，说明诊断过程。     

一类索赔相关风险模型破产概率的研究

本文讨论一类索赔相关同时保费收取为一复合泊松过程的风险模型的破产问题，给出相应的Lundberg不等式．     

排队系统的渐近泊松话务过程

在文中,我们首先给出由马氏过程的一些跳跃时刻形成的简单点过程的有限维分布族弱收敛到泊松过程的相应分布族的条件,并讨论了有限维分布族弱收敛到泊松过程相应分布族的平稳马氏排队系统的话务过程,其次,我们证明了ＧＩ／Ｍ／１排队系统的离去过程的有限维分布族在重话务的情况下弱收敛到泊松过程的相应分布族。     

双复合泊松风险模型下的投资问题

在经典风险模型基础上,研究了保险公司保费收入和索赔均服从复合泊松过程的双复合泊松风险模型,针对最优投资策略和求解破产时刻惩罚金期望折现函数的问题,利用重期望公式和马氏性得到期望折现函数满足的带边界条件的二阶积分微分方程,通过高效的Sinc数值方法求出折现函数的近似数值解,从而由图像分析破产概率变化的趋势.     

G匚W上的泊松群胚结构

从泊松作用的角度考察了群胚上的半直积结构,定义了泊松群胚对泊松群胚的泊松作用,讨论了其性质,并证明了两个泊松群胚的半直积仍是泊松群胚,从而对群胚的半直积结构有了更多的认识.     

跳扩散模型下股价服从几何布朗运动的Esscher变换定价

考虑跳扩散模型下期权的Esscher变换定价,给出了Esscher变换下带跳的B-S矩生成函数和复合泊松过程下的矩生成函数,推导出跳扩散模型下期权的Esscher变换定价公式.     

保险费收取次数为泊松过程下的广义复合泊松风险模型

经典的破产模型是假定保险公司按单位时间常数速率收取保险费，盈余过程{R（t），t≥0中的S（f）=∑i=1^N（t）Y,为一复合泊松过程，本文将保费到达过程推广为一个Poisson过程，同时将S（t）推广为一个广义复合Poisson过程．针对此模型给出了盈余过程的一些性质，得到关于破产概率的一个定理．     

Testing the goodness of fit of a mixed Poisson process

In the literature on the statistical analysis of point processes certain tests for homogeneous Poisson processes are proposed, which in fact are tests for mixed Poisson processes. Some conclusions from this fact are drawn.     

On the problem of testing whether a mixed poisson process is homogeneous

In 2 recent paper Albrecht proposes a test procedure for testing whether a point process is homogeneous, also taking care of alternatives when the process is a mixed Poisson process. In the present note it is argued that it seems impossible to find a meaningful test criterion for testing whether a mixed Poisson process is homogeneous.     

Poisson分布易被忽视的重要性质

"Poisson分布的总体均数与其观察单位成正比",这是一个被忽视的性质,但这是一个很基本的性质,在一些问题的解决中它是必需的.本文讨论了这个性质,并举例说明它在实际问题中的应用,然后对此内容在授课过程中的安排提出建议.     

A Note on the Multivariate Normal Hazard

The ISO* property of noncentrality parameters is derived for the expected value of an ISO* function of independent nonnegative two-parameter compound Poisson random variables and is then applied to unbiasedness of tests and monotonicity of power functions of tests in an order-restricted hypothesis testing problem for the noncentrality parameter. The ISO* property and the Schur convexity are also studied for a class of two-parameter distributions which has the additive property (i.e., is closed under convolution) and contains the one-parameter family with the semigroup property as a special case.     

Two Ergodic Sample-Path Properties of the Poisson Process

For increasing sequences of real numbers we consider two types of asymptotic behavior that remind of the defining property of a (homogeneous) Poisson process according to which the numbers of points in disjoint intervals are independent and follow Poisson distributions with specified parameters. We prove that almost all paths of a Poisson process show this asymptotic behavior, and characterize the Poisson process by these properties. Further we discuss the connection to equidistribution notions.     

Some results for secondary processes generated by a poisson process

We obtain the moment structure of a general class of random variables generated by a Poisson process. We then apply these relationships to several applied probability models. Among these are queues, counter models and low density traffic flow.     

Non-homogeneous space-time fractional Poisson processes

The space-time fractional Poisson process (STFPP), defined by Orsingher and Poilto (2012), is a generalization of the time fractional Poisson process (TFPP) and the space fractional Poisson process (SFPP). We study the fractional generalization of the non-homogeneous Poisson process and call it the non-homogeneous space-time fractional Poisson process (NHSTFPP). We compute their pmf and generating function and investigate the associated differential equation. The limit theorems for the NHSTFPP process are studied. We study the distributional properties, the asymptotic expansion of the correlation function of the non-homogeneous time fractional Poisson process (NHTFPP) and subsequently investigate the long-range dependence (LRD) property of a special NHTFPP. We investigate the limit theorem for the fractional non-homogeneous Poisson process (FNHPP) studied by Leonenko et al. (2014). Finally, we present some simulated sample paths of the NHSTFPP process.     

Prediction in a non-homogeneous Poisson cluster model

A non-homogeneous Poisson cluster model is studied, motivated by insurance applications. The Poisson center process which expresses arrival times of claims, triggers off cluster member processes which correspond to number or amount of payments. The cluster member process is an additive process. Given the past observations of the process we consider expected values of future increments and their mean squared errors, aiming at application in claims reserving problems. Our proposed process can cope with non-homogeneous observations such as the seasonality of claims arrival or the reducing property of payment processes, which are unavailable in the former models where both center and member processes are time homogeneous. Hence results presented in this paper are significant extensions toward applications.     

A Markov Renewal Based Model for Wireless Networks

We propose a queueing network model which can be used for the integration of the mobility and teletraffic aspects that are characteristic of wireless networks. In the general case, the model is an open network of infinite server queues where customers arrive according to a non-homogeneous Poisson process. The movement of a customer in the network is described by a Markov renewal process. Moreover, customers have attributes, such as a teletraffic state, that are driven by continuous time Markov chains and, therefore, change as they move through the network. We investigate the transient and limit number of customers in disjoint sets of nodes and attributes. These turn out to be independent Poisson random variables. We also calculate the covariances of the number of customers in two sets of nodes and attributes at different time epochs. Moreover, we conclude that the arrival process per attribute to a node is the sum of independent Poisson cluster processes and derive its univariate probability generating function. In addition, the arrival process to an outside node of the network is a non-homogeneous Poisson process. We illustrate the applications of the queueing network model and the results derived in a particular wireless network.