Spectral tail processes and max-stable approximations of multivariate regularly varying time series

A regularly varying time series as introduced in Basrak and Segers (2009) is a (multivariate) time series such that all finite dimensional distributions are multivariate regularly varying. The extremal behavior of such a process can then be described by the index of regular variation and the so-called spectral tail process, which is the limiting distribution of the rescaled process, given an extreme event at time 0. As shown in Basrak and Segers (2009), the stationarity of the underlying time series implies a certain structure of the spectral tail process, informally known as the “time change formula”. In this article, we show that on the other hand, every process which satisfies this property is in fact the spectral tail process of an underlying stationary max-stable process. The spectral tail process and the corresponding max-stable process then provide two complementary views on the extremal behavior of a multivariate regularly varying stationary time series.     

Probability density function of the local score position

We calculate the probability density function of the local score position on complete excursions of a reflected Brownian motion. We use the trajectorial decomposition of the standard Brownian bridge to derive two different expressions of the density: the first one is based on a series and an integral while the second one is free off the series.     

Imperfect repair in degradation processes: A Kijima‐type approach

We consider a Wiener process with linear drift for degradation modeling. Regularly, maintenance actions are carried out which produce a reduction of the degradation level. In this paper, we consider the influence of such maintenance actions to the further development of the degradation process and the resulting lifetime distribution. A connection between virtual age in Kijima‐type models and degradation level in the underlying degradation process is developed. Furthermore, estimators for the process parameters as well as for the degree of repair are developed.     

Asymptotic Behaviors for Critical Branching Processes with Immigration

In this paper, we investigate the asymptotic behaviors of the critical branching process with immigration {Z_n, n ≥ 0}. First we get some estimation for the probability generating function of Zn. Based on it, we get a large deviation for Z_(n+1)/Z_n. Lower and upper deviations for Zn are also studied. As a by-product, an upper deviation for max_(1≤i≤n) Z_i is obtained.     

Degradation modeling of 2 fatigue‐crack growth characteristics based on inverse Gaussian processes: A case study

Most modern products that are highly reliable are complex in their inner and outer structures. This situation indicates quality characterization by the interaction of multiple performance characteristics, which motivates the utilization of robust reliability models to obtain robust estimates. It is paramount to obtaining substantial information about a product's life cycle; therefore, when multiple performance characteristics are dependent, it is important to find models that address the joint distribution of performance degradation of such. In this paper, a reliability model for products with 2 fatigue‐crack growth characteristics related to 2 degradation processes is developed. The proposed model considers the dependence among degradation processes by using copula functions considering the marginal degradation processes as inverse Gaussian processes. The statistical inference is performed by using a Bayesian approach to estimate the parameters of the joint bivariate model. A time‐scale transformation is considered to assure monotone paths of the degradation trajectories. The comparison results of the reliability analysis, under both dependent and independent assumptions, are reported with the implementation of the proposed modeling in a case study, which consists of the crack propagation data of 2 terminals of an electronic device.     

一种基于区间过程模型的时变可靠性分析方法

本文提出了一种基于区间过程模型的时变可靠性分析方法来处理涉及区间变量和区间过程的问题.首先,定义一种基于极值响应的可靠性指标来度量区间变量和区间过程不确定性下结构的可靠性.其次,建立并求解一双层优化模型以获得可靠性指标.在内层中,使用EGO方法计算功能函数关于时间的极值响应;在外层中,对极值响应关于原始区间变量和区间过程级数展开获得的区间变量进行优化,以得到其上边界和下边界.最后,通过两个例子以验证本文方法的有效性.     

MDPs with setwise continuous transition probabilities

This paper describes the structure of optimal policies for infinite-state Markov Decision Processes with setwise continuous transition probabilities. The action sets may be noncompact. The objective criteria are either the expected total discounted and undiscounted costs or average costs per unit time. The analysis of optimality equations and inequalities is based on the optimal selection theorem for inf-compact functions introduced in this paper.     

A probabilistic approach to a non‐local quadratic form and its connection to the Neumann boundary condition problem

In this paper we look at a probabilistic approach to a non‐local quadratic form that has lately attracted some interest. This form is related to a recently introduced non‐local normal derivative. The goal is to construct two Markov processes: one corresponding to that form and the other which is related to a probabilistic interpretation of the Neumann problem. We also study the Dirichlet‐to‐Neumann operator for non‐local operators.     

具有工作故障及有限容量的MAP/M/1排队系统性能分析

为了拓展随机排队理论,在具有工作故障的MAP/M/1排队的基础上,引入有限容量策略建立起一个新的排队模型.通过Uniformization Technique将连续时间排队模型转化成对应的离散时间排队模型,运用矩阵几何组合解给出系统中的顾客数量和服务器状态的联合稳态概率表达式,并给出基于稳态概率的性能指标.最后通过一些数值例子展示参数对性能指标的影响.     

基于马尔科夫过程的储备系统稳态性能分析

由于储备系统组成部件在存储期间的失效概率各不相同,当部件状态趋于稳定时,各个状态对系统性能的影响也存在差异。为了识别关键部件及其状态对系统性能的影响程度,本文以重要度为主要指标,应用马尔科夫过程研究储备系统在稳态时的性能变化模式。首先基于综合重要度研究系统性能的变化规律,并结合冷储备系统和温储备系统的状态转移矩阵推导出马尔科夫过程中稳态值的计算方法;其次基于稳态综合重要度获得系统稳态时的性能变化模式;最后以双臂机器人为例,分析部件处于不同状态时对系统性能的影响模式,比较了不同部件综合重要度的变化,验证了提出方法的有效性。