基于交替更新过程的模糊随机破产模型

假设索赔额、盈余额和更新过程均是在模糊随机环境中,并且将索赔过程定义为在交替更新过程.当索赔额和时间间隔是服从不同的指数分布时,本文建立了交替更新过程下的模糊随机破产模型,并给出了最终破产概率公式与最终破产机会均值公式.     

在固定时间抽样的可变抽样区间控制图

本文根据Reynolds在固定时间抽样的可变抽样区间（VSIFT）的x^-控制图^[1]的模型设计中位值x^-和极差R图，规定样本在样等间隔的固定时间点抽取，当过程有变化的迹象时，允许有两个固定时间之间抽取附加样本，本文计算了VSIFTx^~图和R图及联合x^~-R图的发信号前的平均时间，并同固定抽样区间（FSI）的常规x^~和R图作比较，所设计的VSIFTx^~和R图能缩短过程失控时间从而减少不合格品数。     

相关速率

本文讨论两个变量之间的相关速率问题，即：存在着某种函数关系的两个变量，当其中一个变量随着时间发生变化时，另一个变量随时间变化的情况．     

相关速率

本文讨论两个变量之间的相关速率问题,即:存在着某种函数关系的两个变量,当其中一个变量随着时间发生变化时,另一个变量随时间变化的情况.若变量x与y的关系由F(x,y)=0确定,当变量x以一常速率(dxdt为一个常数)随时间t发生变化时,变量y也随时间t发生变化,x与y都可描述为时间t的函     

相关系数与相关性度量

研究了度量相关性的两个主要工具:线性相关系数和尾部相关系数.线性相关系数反映了变量间的线性相关性,这对于一般的椭圆型分布是合适的.但如果随机变量具有不对称的尾部变化特征时,要用尾部相关系数描述它们之间的相关性.通过相关函数C opu la,对沪深股市的尾部相关系数进行了定量分析.结果表明:沪深股市具有较强的相关性.     

有两种故障状态的两部件串联系统的预防维修策略

本文研究的是由两个部件串联组成且有两种故障状态的系统的预防维修策略, 当系统的工作时间达到T时进行预防维修, 预防维修使部件恢复到上一次故障维修后的状态。每个部件发生故障都有两种状态, 可维修和不可维修。当部件的故障为可维修故障时, 修理工对其进行故障维修, 且每次故障维修后的工作时间形成随机递减的几何过程, 每次故障后的维修时间形成随机递增的几何过程。当部件发生N次可维修故障或一次不可维修故障时进行更换。以部件进行预防维修的间隔和更换前的可维修故障次数N组成的二维策略(T, N) 为策略, 利用更新过程和几何过程理论求出了系统经长期运行单位时间内期望费用的表达式, 并给出了具体例子和数值分析。     

两个更新过程叠加的特征问题

N_1(t),N_2(t)是两个独立更新过程,如N(t)=N_1(t)+N_2(t)仍是一更新过程,本文证明了当N_1(t),N_2(t)的间隔分布属于NBUE(NWUE)分布类时,N_1(t),N_2(t),N(t)都是Poisson过程,并改进了Karlin书中的结论。在§2中对更广的具有延迟和镇住时间的两更新过程的叠加问题得到了类似的结论。     

连续与离散时间Gauss次序统计过程的极值

本文研究一类由平稳Gauss过程生成的Gauss次序统计过程的极值与该过程离散化后的极值的渐近关系.结果表明,当Gauss过程是弱相依并且离散化格点足够稀疏时,这两个极值之间是渐近独立的,否则这两个极值之间是渐近相依的.     

结构应力S（t）为X^2—更新过程时最大值概率分布及统计参数的估计

本文讨论结构应力Ｓ（ｔ）在设计基准期（０，Ｔ）内变动规律。当应力变动时间间隔是独立同服从Ｘ＾２－分布的随机变量时，建立Ｘ＾２－更新过程模型，获得Ｘ＾２－更新过程样本函数最大值概率分布的初等函数表达式及最大值ＳＭ的一、二阶矩估计。     

两部件热贮备系统的可靠性分析

本文研究了由两个不同部件组成的热贮备系统。利用Markov更新过程和交替更新过程的方法,求得了(i)系统首次失效时间与其后停工时间的联合分布;(ii)点利用率;(iii)修理工在任一时刻忙的概率;(iv)在(0,t]中系统失效数的分布及其均值。     

Quasi-invariance and integration by parts for determinantal and permanental processes

Determinantal and permanental processes are point processes with a correlation function given by a determinant or a permanent. Their atoms exhibit mutual attraction of repulsion, thus these processes are very far from the uncorrelated situation encountered in Poisson models. We establish a quasi-invariance result: we show that if atom locations are perturbed along a vector field, the resulting process is still a determinantal (respectively permanental) process, the law of which is absolutely continuous with respect to the original distribution. Based on this formula, following Bismut approach of Malliavin calculus, we then give an integration by parts formula.     

Approximate Bayesian Computation and Model Assessment for Repulsive Spatial Point Processes

In many applications involving spatial point patterns, we find evidence of inhibition or repulsion. The most commonly used class of models for such settings are the Gibbs point processes. A recent alternative, at least to the statistical community, is the determinantal point process. Here, we examine model fitting and inference for both of these classes of processes in a Bayesian framework. While usual MCMC model fitting can be available, the algorithms are complex and are not always well behaved. We propose using approximate Bayesian computation (ABC) for such fitting. This approach becomes attractive because, though likelihoods are very challenging to work with for these processes, generation of realizations given parameter values is relatively straightforward. As a result, the ABC fitting approach is well-suited for these models. In addition, such simulation makes them well-suited for posterior predictive inference as well as for model assessment. We provide details for all of the above along with some simulation investigation and an illustrative analysis of a point pattern of tree data exhibiting repulsion. R code and datasets are included in the supplementary material.     

Shuffling algorithm for boxed plane partitions

We introduce discrete time Markov chains that preserve uniform measures on boxed plane partitions. Elementary Markov steps change the size of the box from a×b×c to (a−1)×(b+1)×c or (a+1)×(b−1)×c. Algorithmic realization of each step involves O((a+b)c) operations. One application is an efficient perfect random sampling algorithm for uniformly distributed boxed plane partitions.Trajectories of our Markov chains can be viewed as random point configurations in the three-dimensional lattice. We compute the bulk limits of the correlation functions of the resulting random point process on suitable two-dimensional sections. The limiting correlation functions define a two-dimensional determinantal point processes with certain Gibbs properties.     

Strong convergence of multivariate point processes of exceedances

We study the asymptotic behavior of vectors of point processes of exceedances of random thresholds based on a triangular scheme of random vectors. Multivariate maxima w.r.t. marginal ordering may be regarded as a special case. It is proven that strong convergence—that is convergence of distributions w.r.t. the variational distance—of such multivariate point processes holds if, and only if, strong convergence of multivariate maxima is valid. The limiting process of multivariate point processes of exceedances is built by a certain Poisson process. Auxiliary results concerning upper bounds on the variational distance between vectors of point processes are of interest in its own right.The author was supported by the Deutsche Forschungsgemeinschaft.     

Some time change representations of stable integrals, via predictable transformations of local martingales

From the predictable reduction of a marked point process to Poisson, we derive a similar reduction theorem for purely discontinuous martingales to processes with independent increments. Both results are then used to examine the existence of stochastic integrals with respect to stable Lévy processes, and to prove a variety of time change representations for such integrals. The Knight phenomenon, where possibly dependent but orthogonal processes become independent after individual time changes, emerges as a general principle.     

Moment Solutions for the State Exiting Counting Processes of a Markov Renewal Process

Important performance measures for many Markov renewal processes are the counts of the exits from each state. We present solutions for the conditional first, second, and covariance moments of the state exiting counting processes for a Markov renewal process, and solutions for the unconditional equilibrium versions of the moments. We demonstrate the relationship between the conditional first moments for the state exiting and the state entering counting processes. For analytical and illustrative purposes, we concentrate on the two state case. Two asymptotic expansions for the moment functions are proposed and evaluated both analytically and empirically. The two approximations are shown to be competitive in terms of absolute relative error, but the second approximation has a simpler analytical form which is useful in analyzing more complex stochastic processes having an underlying MRP structure.     

批量马尔可夫到达过程概述

批量马尔可夫到达过程(Batch Markovian Arrival Processes,BMAP)对平稳点过程类具有稠密性,能够描述许多到达过程,在计算机、可靠性、通信和库存等领域的随机建模中获得广泛应用,是一类非常重要的随机点过程.通过对BMAP理论主要文献的分析,系统介绍了BMAP的概念和主要性质,回顾了BMAP应用成果和拟合工作的发展,展望了BMAP理论的发展前景.     

A Point Process Approach to Filtered Processes

We consider some models of filtered point processes such as those developped in Yue and Hashino (2001), and rephrase them in terms of point processes. We derive from this formulation some estimates for the probability of overflow in a rainfall process. This method allows us by considering a non deterministic model of filtering to compute some characteristics of the compound models of Cowpertwait (1994), Phelan (1991), and Rodriguez-Iturbe et al. (1987, 1988). A spatial version of this point process is also studied, using an analogy with the boolean model of stochastic geometry we compute bounds for the probability of dryness in a compound rainfall process.     

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.     

N参数Ornstein-Uhlenbeck过程的点常返性

本文得到了Ｎ参数 Ｏｒｎｓｔｅｉｎ－Ｕｈｌｅｎｂｅｃｋ过程的点常返性准则，我们证明了：若 ｄ＜ ２Ｎ，则ｄ－维 ＯＵＰＮ，Ｘｚ是点常返的；若 ｄ ≥２Ｎ，则Ｘｚ以概率 １不击中点。