Limit theorems for path-functionals of regenerative processes

Regenerative processes were defined and investigated by Smith [12]. These processes have limiting distributions under very mild regularity conditions. In certain applications, such as shot-noise processes and some queueing problems, it is of interest to consider path-functionals of regenerative processes. We seek to extend the nice asymptotic properties of regenerative processes to path-functionals of regenerative processes. We show that these more general processes converge to a “steady-state” process in a certain weak sense. This is applied to show convergence of shot-noise processes. We also present a Blackwell theorem for path-functionals of regenerative processes.     

Measuring deviations from stationarity

Various parameters for measuring the deviation from stationarity for processes belonging to two classes of nonstationarity processes are proposed. Several new results for the two types of processes are obtained. Points of contact are established with the class of oscillatory processes and with the Hamiltonian equation of motion in quantum mechanics. The relation to processes of normal type and to innovations stable processes is also discussed.     

Infinite Divisibility for Stochastic Processes and Time Change

General results concerning infinite divisibility, selfdecomposability, and the class L _m property as properties of stochastic processes are presented. A new concept called temporal selfdecomposability of stochastic processes is introduced. Lévy processes, additive processes, selfsimilar processes, and stationary processes of Ornstein–Uhlenbeck type are studied in relation to these concepts. Further, time change of stochastic processes is studied, where chronometers (stochastic processes that serve to change time) and base processes (processes to be time-changed) are independent but do not, in general, have independent increments. Conditions for inheritance of infinite divisibility and selfdecomposability under time change are given.     

Harmonizable stable processes

Summary This paper examines properties of a class of complex-valued stable processes which have spectral representation by means of independent-increments processes. A representation is derived by an application of Schilder's stochastic integral. Also, another construction of harmonizable stable processes by means of generalized stochastic processes is given, and its relation to the stochastic integral is shown. Some limit theorems of the Fourier transform of a sample from harmonizable stable processes are provided. Moreover, a linear prediction theory which pertains to those processes is suggested as an extension of that of second-order stationary processes.     

Large Deviation Probabilities for Square-Gaussian Stochastic Processes

We investigate properties of square-Gaussian stochastic processes. These processes are formed by quadratic forms of Gaussian processes or by limits in the mean square of quadratic forms of Gaussian processes. Special classes of these processes are determined and investigated. For processes from these classes estimates of large deviation probability are obtained. These estimates we use to estimate the probability that Gaussian vector-valued process leave some region on some interval of time. We construct asymptotic confidence regions for estimates of covariance functions of vector-valued Gaussian processes. Criterion of hypothesis testing on covariance functions of these processes is constructed.     

What is a multi-parameter renewal process?

The concept of the renewal property is extended to processes indexed by a multidimensional time parameter. The definition given includes not only partial sum processes, but also Poisson processes and many other point processes whose jump points are not totally ordered. A new version of the waiting time paradox is proven for multidimensional Poisson processes, and is shown to imply the renewal property. Finally, martingale properties of renewal processes are studied.     

Semi-Selfsimilar Processes

A notion of semi-selfsimilarity of R ^d -valued stochastic processes is introduced as a natural extension of the selfsimilarity. Several topics on semi-selfsimilar processes are studied: the existence of the exponent for semi-selfsimilar processes; characterization of semi-selfsimilar processes as scaling limits; relationship between semi-selfsimilar processes with independent increments and semi-selfdecomposable distributions, and examples; construction of semi-selfsimilar processes with stationary increments; and extension of the Lamperti transformation. Semi-stable processes where all joint distributions are multivariate semi-stable are also discussed in connection with semi-selfsimilar processes. A wide-sense semi-selfsimilarity is defined and shown to be reducible to semi-selfsimilarity.     

THE STATIONARY DIFFUSION PROCESSES GENERATED BY SECOND ORDER DIFFERENTIAL OPERATIONS AND THEIR PROBABILITY CURRENTS

In this paper,we are concerned with the stationary Markov processes generated by second order differential operators under the local boundary conditions, It is proved that all those processes have constnt probability currents, known as circulations of the processes, and hence the processes are called single circulation processes. The invariant measures and the circulation values of those processes are calculated in all cases of boundary classification. It is shown that thr circulation value is an elementary characteristic of irreversible stationary Markov processes and that all the reversible Markov processes in the same problem are just the special ones of the single circulation processes whose circulation values are equal to zero and whose ergodic limits in the sense of weak convergence are not trivial.     

Stochastic order for alpha-permanental point processes

We establish relations of stochastic comparison among point processes elements of the set of alpha-permanental point processes. This set contains in particular, the determinantal point processes, the Poisson point processes and the permanental point processes. We show that these three classes of point processes can be ordered according to the increasing stochastic order. Elementary particles provide illustrations of some of the obtained relations of stochastic comparison.     

Asymptotic behavior of weakly dependent aggregated processes

Aggregated processes appear in many areas of statistics, natural sciences and economics and studying their behavior has a considerable importance from a purely probabilistic point of view as well. Granger (1980) showed that aggregating processes of simple structure can lead to processes with much more complex dynamics, in particular, aggregating random coefficient AR(1) processes can result in long memory processes. This opens a new way to analyze complex processes by constructing such processes from simple ‘building blocks’ via aggregation.     

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．     

Spatial autoregressive and moving average Hilbertian processes

This paper addresses the introduction and study of structural properties of Hilbert-valued spatial autoregressive processes (SARH(1) processes), and Hilbert-valued spatial moving average processes (SMAH(1) processes), with innovations given by two-parameter (spatial) matingale differences. For inference purposes, the conditions under which the tensorial product of standard autoregressive Hilbertian (ARH(1)) processes (respectively, of standard moving average Hilbertian (MAH(1)) processes) is a standard SARH(1) process (respectively, it is a standard SMAH(1) process) are studied. Examples related to the spatial functional observation of two-parameter Markov and diffusion processes are provided. Some open research lines are described in relation to the formulation of SARMAH processes, as well as General Spatial Linear Processes in Functional Spaces.     

每个节点具有多服务台的Jackson网络流体逼近的收敛速度

研究一个每个节点具有多服务台的Jackson网络.在服务强度为1的条件下,研究了Jackson网络的泛函重对数率与其流体逼近的收敛速度,证明了如果该网络的外部到达过程,服务过程有泛函重对数率,且在流体变换下以指数速度收敛到其相应的流体模型,则其队长过程、负荷过程、忙期过程等也具有相应的性质.     

Generation of self-similar processes for simulation studies of telecommunication networks

It is generally accepted that self-similar processes may provide better models for teletraffic in modern telecommunication networks than Poisson processes. If stochastic self-similarity of teletraffic is not taken into account, it can lead to inaccurate conclusions about the performance of networks. Thus, an important requirement for conducting simulation studies of networks is the ability to generate long synthetic self-similar sequences of incremental processes, to transform them into interevent time intervals, and to do this accurately and quickly. A fast generator for count processes based on wavelets is described. Then a method for transformation of count processes into interevent processes proposed by Leroux and Hassan [1] and an alternative method, that is, inverting the empirical distribution directly, are studied. A case study is discussed to show how long sequences are needed in the steady-state simulation of queueing models with self-similar input processes. This is compared with simulation run lengths of the same queueing models fed by Poisson processes.     

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.     

Self-similarity and Lamperti convergence for families of stochastic processes

We define a new type of self-similarity for one-parameter families of stochastic processes, which applies to certain important families of processes that are not self-similar in the conventional sense. This includes Hougaard Lévy processes such as the Poisson processes, Brownian motions with drift and the inverse Gaussian processes, and some new fractional Hougaard motions defined as moving averages of Hougaard Lévy process. Such families have many properties in common with ordinary self-similar processes, including the form of their covariance functions, and the fact that they appear as limits in a Lamperti-type limit theorem for families of stochastic processes.     

On permanental processes

Permanental processes can be viewed as a generalization of squared centered Gaussian processes. We analyze the connections of these processes with the local time process of general Markov processes. The obtained results are related to the notion of infinite divisibility.     

Diffusion approximation for storage processes

For a sequence of storage processes with general release rate functions which contain, as a special case, queuing processes, we show that under appropriate conditions, suitably normalized processes for storage processes converge to diffusions in the sense of law.     

On Feller's boundary problem for Markov processes in weak duality

We give an affirmative answer to Feller's boundary problem going back to 1957 by obtaining a resolvent characterization for the duality preserving extensions of a pair of standard Markov processes in weak duality (minimal processes) to the boundary consisting of countably many points. Our resolvent characterization involves the resolvents for the minimal processes, the Feller measures that are intrinsic to the minimal processes as well as the restrictions to the boundary of the jumping and killing measures of the extension processes. Conversely, given killing rates on the boundary, we construct the corresponding duality preserving extensions of the minimal processes that admit no jumps between the boundary points and have the prescribed killing rate at the boundary, by repeatedly doing one-point extension one at a time using Itô's Poisson point processes of excursions.     

关于截断型分布族中估计的经验过程的渐近分布的进一步研究

但是,若分布 F 中含有未知参数θ,即 F=F(x;θ),那么为计算经验过程,就必须对θ进行适当的估计,把估计(?)_n 代入(2),(1)中,便得到一估计的经验过程(?)_n(t)。那么,这一估计的经验过程的渐近分布如何?Durbin 研究了这一问题。对一般的分布族 F(x;θ),θ∈(?),在一定的假设条件下(主要是所谓条件 A_2),他证明了这一估计的经验过程(?)(t)其渐近过程是一较复杂的正态过程,这个正态过程一般是依赖于 F 的,甚至依赖于未知参数θ的。但该文指出,当θ是位置、刻度参数时,渐近过程可与θ无关。尔后,Durbin,Schneider 等又具体地研究了指数分布族、Gamma 分布族,得到具体结果,