Iterative procedures for solutions of random operator equations in Banach spaces

We construct random iterative processes for weakly contractive and asymptotically nonexpansive random operators and study necessary conditions for the convergence of these processes. It is shown that they converge to the random fixed points of these operators in the setting of Banach spaces. We also proved that an implicit random iterative process converges to the common random fixed point of a finite family of asymptotically quasi-nonexpansive random operators in uniformly convex Banach spaces.     

平稳随机过程的小波分析方法

利用小波变换对平稳随机过程进行了谱分析,在小波变换的基础上给出了平稳随机过程的时—频功率谱及联合平稳随机过程的时—频互功率谱的概念,并详尽地研究了它们所具有的性质及与传统功率谱的关系。     

Supermodular Comparison of Time-to-Ruin Random Vectors

This paper studies time-to-ruin random vectors for multivariate risk processes. Two cases are considered: risk processes with independent increments and risk processes evolving in a common random environment (e.g., because they share the same economic conditions). As expected, increasing the dependence between the risk processes increases the dependence between their respective time-to-ruin random variables. This article is dedicated to the memory of our beloved friend Benjamin Zeev Levikson who passed away on July 16, 2005.     

On finiteness and continuity of shot noise processes

For a rather general class of stochastic processes induced by time-stationary and by event-stationary random marked point processes, respectively, conditions are given for the almost sure finiteness of these processes and for their continuous dependence on the underlying random marked point process.     

Gaussian and sparse processes are limits of generalized Poisson processes

The theory of sparse stochastic processes offers a broad class of statistical models to study signals, far beyond the more classical class of Gaussian processes. In this framework, signals are represented as realizations of random processes that are solution of linear stochastic differential equations driven by Lévy white noises. Among these processes, generalized Poisson processes based on compound-Poisson noises admit an interpretation as random L-splines with random knots and weights. We demonstrate that every generalized Lévy process—from Gaussian to sparse—can be understood as the limit in law of a sequence of generalized Poisson processes. This enables a new conceptual understanding of sparse processes and suggests simple algorithms for the numerical generation of such objects.     

Random sets. A survey of results and applications

A survey of current directions in the theory of random closed sets is presented; these include: the central limit theorem, the law of large numbers for Minkowski sums and unions of random sets, semi-Markov random closed sets, Boolean models and statistical estimation of their parameters, specification of distributions and associated problems of capacity theory. Weak convergence of random closed sets is defined and its application to limit theorems for graphs and epi-graphs of random processes and problems of stochastic optimization is described. Other connections with the theory of random processes (level sets, multivalued and controllable random processes) are also discussed.Translated from Ukrainskii Matematicheskii Zhurnal, Vol. 43, No. 12, pp. 1587–1599, December, 1991.     

带随机过程的随机规划问题最优解过程的平稳性与马氏性

证明了带随机过程的随机规划问题其最优争集中至少存在一列最优解均为可测的随机过程；且如果问题中的随机过程具有平稳性与马氏性，则此时间问题的最优解过程亦具有相应的特性。     

Pseudo-Poissonian processes with stochastic intensity and a class of processes generalizing the Ornstein–Uhlenbeck process

The definition of pseudo-Poissonian processes is given in the famous monograph of William Feller (1971, Vol. II, Chapter X). The contemporary development of the theory of information flows generates new interest in the detailed analysis of behavior and characteristics of pseudo-Poissonian processes. Formally, a pseudo-Poissonian process is a Poissonian subordination of the mathematical time of an independent random sequence (the time randomization of a random sequence). We consider a sequence consisting of independent identically distributed random variables with second moments. In this case, pseudo-Poissonian processes do not have independent increments, but it is possible to calculate the autocovariance function, and it turns out that it exponentially decreases. Appropriately normed sums of independent copies of such pseudo-Poissonian processes tend to the Ornstein–Uhlenbeck process. A generalization of driving Poissonian processes to the case where the intensity is random is considered and it is shown that, under this generalization, the autocovariance function of the corresponding pseudo-Poissonian process is the Laplace transform of the distribution of that random intensity. Stochastic choice principles for the distribution of the random intensity are shortly discussed and they are illustrated by two detailed examples.     

Precise Large Deviations for Long-Tailed Distributions

In this paper, we investigate the precise large deviations for sums of independent identically distributed random variables with heavy-tailed distributions. We prove asymptotic relations for non-random sums and for random sums of random variables with long-tailed distributions. We apply the results on two useful counting processes, namely, renewal and compound-renewal processes.     

广生灭过程的遍历性及平稳分布

文献[1]研究了广生灭过程的向上积分型随机泛函，得到了广生灭过程的若干数字特征以及常返的充要条件，该文讨论广生灭过程向下积分型随机泛函，给出了广生灭过程遍历的充要条件以及平均返回时间的计算公式，并在遍历的条件下求出了广生灭过程的平稳分布．     

On convergence of random walks generated by compound Cox processes to Lévy processes

A functional limit theorem is proved establishing weak convergence of random walks generated by compound doubly stochastic Poisson processes to Lévy processes in the Skorokhod space. As corollaries, theorems are proved on convergence of random walks with jumps having finite variances to Lévy processes with mixed normal distributions, and in particular, to stable Lévy processes.     

Analytic stochastic process solutions of second-order random differential equations

In this work, trigonometric stochastic processes arise as mean square solutions of random differential equations, using a random Fröbenius method. Important operational properties of the trigonometric stochastic processes are established.     

A kriging procedure for processes indexed by graphs

We provide a new kriging procedure of processes on graphs. Based on the construction of Gaussian random processes indexed by graphs, we extend to this framework the usual linear prediction method for spatial random fields, known as kriging. We provide the expression of the estimator of such a random field at unobserved locations as well as a control for the prediction error.     

随机环境中依赖年龄分枝过程的爆炸问题

讨论了随机环境中依赖年龄分枝过程中的爆炸问题,得到了过程爆炸的判定定理以及关于两个过程爆炸的比较定理.     

Random capacities and their distributions

Summary We formalize the notion of an increasing and outer continuous random process, indexed by a class of compact sets, that maps the empty set on zero. Existence and convergence theorems for distributions of such processes are proved. These results generalize or are similar to those known in the special cases of random measures, random (closed) sets and random (upper) semicontinuous functions. For the latter processes infinite divisibility under the maximum is introduced and characterized. Our result generalizes known characterizations of infinite divisibility for random sets and max-infinite divisibility for random vectors. Also discussed is the convergence in distribution of the row-vise maxima of a null-array of random semicontinuous functions.Research supported by the Swedish Natural Science Research Council     

线性过程的强逼近和重对数律

本文讨论由独立同分布随机变量列产生的线性过程的泛函型重对数律和强逼近, 同时又给出由NA随机变量列产生的线性过程的重对数律.     

Convergence of random step lines to Ornstein-Uhlenbeck-type processes

The paper deals with random step-line processes defined by sums of independent identically distributed random variables multiplied by independent indicators. These processes describe some models in which random variables are replaced with other ones. We prove the convergence in distribution of such processes to the weighted Ornstein-Uhlenbeck process. Supported by the Hungarian Foundation for Scientific Research (grant No. OTKA-T016933-1996) and by the Hungarian Ministry of Culture and Education (grant No. 179-1995). Proceedings of the Seminar on Stability Problems for Stochastic Models, Hajdúszoboszló, Hungary, 1997, Part I.     

Positive dependence orderings and stopping times

We study the positive dependence of pairs of stochastic processes and examine its relation with the properties of certain stopping times. Some special cases, such as dependent random walks, Gaussian processes and exchangeable sequences of elliptically contoured random variables, are taken into account.     

Super-Tree Random Measures

We use supercritical branching processes with random walk steps of geometrically decreasing size to construct random measures. Special cases of our construction give close relatives of the super-(spherically symmetric stable) processes. However, other cases can produce measures with very smooth densities in any dimension.     

Quenched invariance principle for simple random walk on discrete point processes

We consider the simple random walk on random graphs generated by discrete point processes. This random walk moves on graphs whose vertex set is a random subset of a cubic lattice and whose edges are lines between any consecutive vertices on lines parallel to each coordinate axis. Under the assumption that the discrete point processes are finitely dependent and stationary, we prove that the quenched invariance principle holds, i.e., for almost every configuration of the point process, the path distribution of the walk converges weakly to that of a Brownian motion.