Stable Central Limit Theorems for Super Ornstein–Uhlenbeck Processes, Ⅱ

This paper is a continuation of our recent paper(Electron. J. Probab., 24(141),(2019)) and is devoted to the asymptotic behavior of a class of supercritical super Ornstein–Uhlenbeck processes(X_t)_t≥0 with branching mechanisms of infinite second moments. In the aforementioned paper, we proved stable central limit theorems for X_t(f) for some functions f of polynomial growth in three different regimes. However, we were not able to prove central limit theorems for X     

Limit Theorems for Multiplicative Processes

Let W be a non-negative random variable with EW=1, and let {W _i } be a family of independent copies of W, indexed by all the finite sequences i=i ₁i _n of positive integers. For fixed r and n the random multiplicative measure ⁿ _r has, on each r-adic interval at nth level, the density with respect to the Lebesgue measure on [0,1]. If EW log Wr, the sequence { ⁿ _r } _n converges a.s. weakly to the Mandelbrot measure _r . For each fixed 1n, we study asymptotic properties for the sequence of random measures { ⁿ _r } _r as r. We prove uniform laws of large numbers, functional central limit theorems, a functional law of iterated logarithm, and large deviation principles. The function-indexed processes is a natural extension to a tree-indexed process at nth level of the usual smoothed partial-sum process corresponding to n=1. The results extend the classical ones for { ¹ _r } _r , and the recent ones for the masses of { _r } _r established in Ref. 23.     

Central Limit Theorems for Level Functionals of Stationary Gaussian Processes and Fields

We introduce a general method, which combines the one developed by authors in 1997 and one derived from the work of Malevich,⁽¹⁷⁾ Cuzick⁽⁷⁾ and mainly Berman,⁽³⁾ to provide in an easy way a CLT for level functionals of a Gaussian process, as well as a CLT for the length of a level curve of a Gaussian field.     

New Central Limit Theorems for Functionals of Gaussian Processes and their Applications

As a consequence of the seminal work of Nualart and Peccati in 2005 we have new central limit theorems for functional of Gaussian processes that have allowed us to elucidate the asymptotic behavior of the multipower variation of certain ambit processes, see Barndorff-Nielsen et al. (2009c). This survey intends to explain the role of the Malliavin calculus to reach these results.     

Approximate Central Limit Theorems

We refine the classical Lindeberg–Feller central limit theorem by obtaining asymptotic bounds on the Kolmogorov distance, the Wasserstein distance, and the parameterized Prokhorov distances in terms of a Lindeberg index. We thus obtain more general approximate central limit theorems, which roughly state that the row-wise sums of a triangular array are approximately asymptotically normal if the array approximately satisfies Lindeberg’s condition. This allows us to continue to provide information in nonstandard settings in which the classical central limit theorem fails to hold. Stein’s method plays a key role in the development of this theory.     

Functional Limit Theorems for Compound Renewal Processes

Siberian Mathematical Journal - We generalize Anscombe’s Theorem to the case of stochastic processes converging to a continuous random process. As applications, we find a simple proof of an...     

Central Limit Theorems for Markov-Connected Random Variables

The paper provides some central limit theorems for triangular arrays of Markov-connected random variables. It is assumed the Markov chain to satisfy condition (D₁) which is an generalization of strong Doeblin's condition (D_o). One result represents a central limit theorem without the assumption of finite variances.     

Central Limit Theorems for Gromov Hyperbolic Groups

In this paper we study asymptotic properties of symmetric and nondegenerate random walks on transient hyperbolic groups. We prove a central limit theorem and a law of iterated logarithm for the drift of a random walk, extending previous results by S. Sawyer and T. Steger and of F. Ledrappier for certain CAT(−1)-groups. The proofs use a result by A. Ancona on the identification of the Martin boundary of a hyperbolic group with its Gromov boundary. We also give a new interpretation, in terms of Hilbert metrics, of the Green metric, first introduced by S. Brofferio and S. Blachère.     

Central Limit Theorems for Multiple Skorokhod Integrals

In this paper, we prove a central limit theorem for a sequence of multiple Skorokhod integrals using the techniques of Malliavin calculus. The convergence is stable, and the limit is a conditionally Gaussian random variable. Some applications to sequences of multiple stochastic integrals, and renormalized weighted Hermite variations of the fractional Brownian motion are discussed.     

Strong Limit Theorems for Increments of Renewal Processes

We study the almost sure behavior of increments of renewal processes. We derive a universal form of norming functions in the strong limit theorems for increments of such processes. This result unifies the following well-known theorems for increments of renewal processes: the strong law of large numbers, Erdos-Renyi law, Csorgo-Revesz law, and law of the iterated logarithm. New results are obtained for processes with distributions of renewal times from domains of attraction of the normal law and completely asymmetric stable laws with index (1, 2). Bibliography: 15 titles.__________Translated from Zapiski Nauchnykh Seminarov POMI, Vol. 298, 2003, pp. 208–225.     

Functional Central Limit Theorems for Supercritical Superprocesses

In this paper, we establish some functional central limit theorems for a large class of general supercritical superprocesses with spatially dependent branching mechanisms satisfying a second moment condition. In the particular case when the state \(E\) is a finite set and the underlying motion is an irreducible Markov chain on \(E\), our results are superprocess analogs of the functional central limit theorems of Janson (Stoch. Process. Appl. 110:177–245, 2004) for supercritical multitype branching processes. The results of this paper are refinements of the central limit theorems in Ren et al. (Stoch. Process. Appl. 125:428–457, 2015).     

Some Limit Theorems in Geometric Processes

Geometric process (GP) was introduced by Lam[4,5], it is defined as a stochastic process {Xn, n = 1, 2,…} for which there exists a real number a > 0, such that {an-1 Xn, n = 1,2, …} forms a renewal process (RP). In this paper, we study some limit theorems in GP. We first derive the Wald equation for GP and then obtain the limit theorems of the age, residual life and the total life at t for a GP. A general limit theorem for Sn with a > 1 is also studied. Furthermore, we make a comparison between GP and RP, including the comparison of their limit distributions of the age, residual life and the total life at t.     

带移民Jirina过程的弱极限定理

该文在矩条件下讨论了一列带移民Jirina过程的弱极限定理.按照极限过程的不同对矩条件作了简单分类.文章证明了在不同的矩条件下,一列带移民Jirina过程适当规范后可以在Skorokhod空间分别弱收敛到连续分支过程,带移民的连续分支过程,不连续的带移民分支过程以及确定性过程.对最后这种情形,还给出了一个波动极限定理.     

Strong Law of Large Numbers and Central Limit Theorems for Functionals of Inhomogeneous Semi-Markov Processes

Limit theorems for functionals of classical (homogeneous) Markov renewal and semi-Markov processes have been known for a long time, since the pioneering work of Pyke Schaufele (Limit theorems for Markov renewal processes, Ann. Math. Statist., 35(4):1746–1764, 1964). Since then, these processes, as well as their time-inhomogeneous generalizations, have found many applications, for example, in finance and insurance. Unfortunately, no limit theorems have been obtained for functionals of inhomogeneous Markov renewal and semi-Markov processes as of today, to the best of the authors’ knowledge. In this article, we provide strong law of large numbers and central limit theorem results for such processes. In particular, we make an important connection of our results with the theory of ergodicity of inhomogeneous Markov chains. Finally, we provide an application to risk processes used in insurance by considering a inhomogeneous semi-Markov version of the well-known continuous-time Markov chain model, widely used in the literature.     

Functional Central Limit Theorems for Triangular Arrays of Function-Indexed Processes under Uniformly Integrable Entropy Conditions

Functional central limit theorems for triangular arrays of rowwise independent stochastic processes are established by a method replacing tail probabilities by expectations throughout. The main tool is a maximal inequality based on a preliminary version proved by P. Gaenssler and Th. Schlumprecht. Its essential refinement used here is achieved by an additional inequality due to M. Ledoux and M. Talagrand. The entropy condition emerging in our theorems was introduced by K. S. Alexander, whose functional central limit theorem for so-calledmeasure-like processeswill be also regained. Applications concern, in particular, so-calledrandom measure processeswhich include function-indexed empirical processes and partial-sum processes (with random or fixed locations). In this context, we obtain generalizations of results due to K. S. Alexander, M. A. Arcones, P. Gaenssler, and K. Ziegler. Further examples include nonparametric regression and intensity estimation for spatial Poisson processes.     

一类带移民超α-对称稳定过程的中心极限定理

证明一类带移民超α-对称稳定过程及其占位时过程在各种维数下的中心极限定理,得到了它们的中心化过程均依分布收敛于S'(Rd)值的中心型高斯随机变量.     

Central Limit Theorems for Supercritical Superprocesses with Immigration

In this paper, we establish a central limit theorem for a large class of general supercritical superprocesses with immigration with spatially dependent branching mechanisms satisfying a second moment condition. This central limit theorem extends and generalizes the results obtained by Ren et al. (Stoch Process Appl 125:428–457, 2015). We first give laws of large numbers for supercritical superprocesses with immigration since there are few convergence results on immigration superprocesses, then based on these results, we establish the central limit theorem.     

Some Limit Theorems for Extremal and Union Shot-Noise Processes

We study the limiting behaviour of suitably normalized union shot-noise processes , where F is a set-valued function on R^d × ?? is a sequence of i.i.d. random elements on some measurable space [?? ??] and Ψ = {x_i, i≥ 1} stands for a stationary d-dimensional point process whose intensity λ tends to infinity. General results concerning weak convergence of parametrized union shot-noise processes Ξ?(t) as ? ↓ 0 are obtained (Theorem 5.1 and its corollaries), if the point process λ^{1 d}Ψ has a weak limit and F satisfies some technical conditions. An essential tool for proving these results is the notion of regular variation of multivalued functions. Some examples illustrate the applicability of the results.     

Limit Theorems for Maxima of Sums and Renewal Processes

Let {X_i}_i=1,2,... be a sequence of i.i.d. random variables, let S_n = X₁ + ... + X_n, and let S_n a.s. We discuss necessary and sufficient conditions for the Kolmogorov and Marcinkiewicz–Zygmund type strong laws of large numbers and for the law of the iterated logarithm for renewal processes defined in two different ways. Bibliography: 16 titles.