Limit theorems for permutations of empirical processes with applications to change point analysis

Theorems of approximation of Gaussian processes for the sequential empirical process of the permutations of independent random variables are established. The results are applied to simulate critical values for the functionals of sequential empirical processes used in change point analysis. The proofs are based on the properties of rank statistics and negatively associated random variables.     

Limit theorems for branching Markov processes

We establish almost sure limit theorems for a branching symmetric Hunt process in terms of the principal eigenvalue and the ground state of an associated Schrödinger operator. Here the branching rate and the branching mechanism can be state-dependent. In particular, the branching rate can be a measure belonging to a certain Kato class and is allowed to be singular with respect to the symmetrizing measure for the underlying Hunt process X. The almost sure limit theorems are established under the assumption that the associated Schrödinger operator of X has a spectral gap. Such an assumption is satisfied if the underlying process X is a Brownian motion, a symmetric α-stable-like process on or a relativistic symmetric stable process on .     

Limit theorems with refinements for random processes

One considers the problem of the derivation of limit theorems with refinements in functional spaces. One proves theorems on the expansions of the mathematical expectations of bounded continuous linear functionals of the trajectories of a Gaussian random process. From these theorems one derives a limit theorem with correction terms for the mathematical expectation of a functional of the trajectories of the time-discretized Wiener process, when the step of the discretization tends to zero. One discusses questions regarding generalizations, methods of proof, and the relation of these kind of limit theorems with other problems of the theory of probability, as well as possible applications of these theorems.Translated from Veroyatnostnye Raspredeleniya i Matematicheskaya Statistika, pp. 94–114, 1986.     

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.     

Limit theorems for diffusion-type processes inR m

For a sequence of stochastic equations of diffusion type, conditions that are close to necessary and sufficient ones are established for the weak convergence of measures ,n=1, ... , associated with the solutions, to the limiting measure . The conditions under which the weak convergence of the solutions of stochastic equations implies their strong convergence are established as well.Translated from Ukrainskii Matematicheskii Zhurnal, Vol. 45, No. 10, pp. 1371–1378, October, 1993.     

Limit theorems for recurrent semi-Markov processes and Markov renewal processes

For Harris recurrent Markov renewal processes and semi-Markov processes one obtains a central limit theorem. One also obtains Berry-Esseen type estimates for this theorem. Their proof is based on the Kolmogorov-Doeblin regenerative method.Translated from Zapiski Nauchnykh Seminarov Leningradskogo Otdeleniya Matematicheskogo Instituta im. V. A. Steklova AN SSSR, Vol. 142, pp. 86–97, 1985.     

Limit theorems for a class of diffusion processes

We consider a diffusion process {x(t)} on a compact Riemannian manifold with generator δ/2 + b. A current‐valued continuous stochastic process {X _t} in the sense of Itô [8] corresponds to {x(t)} by considering the stochastic line integral X _t(a) along {x(t)} for every smooth 1-form a. Furthermore {X _t} is decomposed into the martingale part and the bounded variation part as a current-valued continuous process. We show the central limit theorems for {X _t} and the martingale part of {X _t}. Occupation time laws for recurrent diffusions and homogenization problems of periodic diffusions are closely related to these theorems     

Limit theorems for increments of compound renewal processes

We derive universal strong limit theorems for increments of compound renewal processes which unify the strong law of large numbers, Erd?s-Rényi law, Csörg?-Révész law, and law of the iterated logarithm for such processes. New results are obtained under various moment assumptions on distributions of random variables generating the process. In particular, we study the case of distributions from domains of attraction of the normal law and completely asymmetric stable laws with index α ∈ (1, 2). Bibliography: 15 titles.     

L ∞ — Limit theorems for Markov processes

A necessary and sufficient condition for convergence of Markov processesL _∞ is given. As a consequence we get a theorem concerning the convergence of Harris processes. This paper is a part of the author’s Ph.D. thesis to be submitted to the Hebrew University of Jerusalem. The author wishes to express his thanks to Professor S. R. Foguel for much valuable advice and encouragement.     

Limit theorems for multitype continuous time Markov branching processes

Summary Let X(t)=(X ₁ (t), X ₂ (t), , X _t (t)) be a k-type (2k<) continuous time, supercritical, nonsingular, positively regular Markov branching process. Let M(t)=((m _ij (t))) be the mean matrix where m _ij (t)=E(X _j (t)¦X _r (0)= _ir for r=1, 2, , k) and write M(t)=exp(At). Let be an eigenvector of A corresponding to an eigenvalue . Assuming second moments this paper studies the limit behavior as t of the stochastic process . It is shown that i) if 2 Re >₁, then · X(t)e{–t¦ converges a.s. and in mean square to a random variable. ii) if 2 Re ₁ then [ · X(t)] f(v · X(t)) converges in law to a normal distribution where f(x)=(x) ^–1 if 2 Re <₁ and f(x)=(x log x)^–1 if 2 Re =₁, ₁ the largest real eigenvalue of A and v the corresponding right eigenvector.Research supported in part under contracts N0014-67-A-0112-0015 and NIH USPHS 10452 at Stanford University.     

Limit theorems for the integrals of some branching processes

A number of limit theorems for the integral of a non-supercritical age-dependent branching process with immigration are found. Some results are given for the subcritical case without immigration, but conditioned to stay positive. Finally a central limit theorem is given for the population size of the subcritical immigration set up under a condition when no limiting distribution exists.     

Limit theorems for random processes with random time substitution

In this paper we prove a theorem on sufficient conditions for the convergence in the Skorokhod space D[0, 1] of a sequence of random processes with random time substitution. We obtain almost sure versions of this theorem.     

Limit theorems for functionals of two independent Gaussian processes

Under certain mild conditions, some limit theorems for functionals of two independent Gaussian processes are obtained. The results apply to general Gaussian processes including fractional Brownian motion, sub-fractional Brownian motion and bi-fractional Brownian motion. A new and interesting phenomenon is that, in comparison with the results for fractional Brownian motion, extra randomness appears in the limiting distributions for Gaussian processes with nonstationary increments, say sub-fractional Brownian motion and bi-fractional Brownian. The results are obtained based on the method of moments, in which Fourier analysis, the chaining argument introduced in [11] and a pairing technique are employed.