Asymptotic expansions in the integral and local limit theorems in banach spaces with applications to ω-statistics

LetB be a real separable Banach space and letX,X ₁,X ₂,...∈B denote a sequence of independent identically distributed random variables taking values inB. DenoteS _n =n ^?1/2(X ₁+...X _n ). Let π:B→R be a polynomial. We consider (truncated) Edgeworth expansions and other asymptotic expansions for the distribution function of the r.v. π(S _n ) with uniform and nonuniform bounds for the remainder terms. Expansions for the density of π(S _n ) and its higher order derivatives are derived as well. As an application of the general results we get expansions in the integral and local limit theorems for ω-statistics $$\omega _n^p (q)\mathop { = n^{{p \mathord{\left/ {\vphantom {p 2}} \right. \kern-\nulldelimiterspace} 2}} }\limits^\Delta \smallint _{(0,1)} \{ F_n (x) - x\} ^p q(x)dx$$ and investigate smoothness properties of their distribution functions. Herep≥2 is an even number,q: [0, 1]→[0, ∞] is a measurable weight function, andF _n denotes the empirical distribution function. Roughly speaking, we show that in order to get an asymptotic expansion with remainder termO(n ^?α), α<p/2, for the distribution function of the ω-statistic, it is sufficient thatq is nontrivial, i.e., mes{t∈(0, 1):q(t)≠0}>0. Expansions of arbitrary length are available provided the weight functionq is absolutely continuous and positive on an nonempty subinterval of (0, 1). Similar results hold for the density of the distribution function and its derivatives providedq satisfies certain very mild smoothness condition and is bounded away from zero. The last condition is essential since the distribution function of the ω-statistic has no density whenq is vanishing on an nonempty subinterval of (0, 1).     

Functional limit theorems for Galton–Watson processes with very active immigration

We prove weak convergence on the Skorokhod space of Galton–Watson processes with immigration, properly normalized, under the assumption that the tail of the immigration distribution has a logarithmic decay. The limits are extremal shot noise processes. By considering marginal distributions, we recover the results of Pakes (1979).     

Approximation processes for fourier-jacobi expansions †

This paper deals with the approximation theoretic aspects of summation methods for expansions in terms of Jacobi polynomials. When a funcation f is expanded in a Fourier-Jacobi series, many summation methods for this series may be looked upon as approximation processes for the function f. The main object of this paper is to investigate the order of approximation of these processes and to characterize the functions which allow a certain order of approximation. Many of these processes exhibit the phenomenon of saturation, which is equivalent to the existence of an optimal order of approximation (the saturation, which is equivalent to the existence of an optimal order of approximation (the saturation order). For the approximation processes treated in this paper the saturation order and the saturation class, that is the class if functions which can be approximated with the optimal order, are derived. The characterization of the classes of functions is accomplished by means of the theory of intermediate spaces due to Peetre[19] (compare Butzer and Berens [7]). Another basic tool in this work is the convolution structure for Jacobi series, introduced by Askey and Wainger [1] (see also Gasper [14], {15})     

Szegö limit theorems in quantum mechanics

We prove a Szegö-type theorem for some Schrödinger operators of the form $\text{H =}\text{?1}\text{2Δ}\text{+ V}$ with V smooth, positive and growing like $\text{V}{}_0\text{¦x¦}{}^{\mathrm{k}}\text{, k > 0}$. Namely, let π_λ be the orthogonal projection of L² onto the space of the eigenfunctions of H with eigenvalue ?λ; let A be a 0th order self-adjoint pseudo-differential operator relative to Beals-Fefferman weights $\text{?(x, ξ) = 1, Φ(x, ξ) = (1 + ¦ξ¦}{}^2\text{+ V(x))}{}^{\mathrm{<mtext>1</mtext><mtext>2</mtext>}}$ and with total symbol a(x, ξ); and let f∈C($\text{R}$). Then

$\text{lim}\text{λ→∞}\text{1}\text{rank}\text{π}{}_{\mathrm{\lambda }}\text{tr}\text{f(π}{}_{\mathrm{\lambda }}\text{Aπ}{}_{\mathrm{\lambda }}\text{)=}\text{lim}\text{λ→∞}\text{1}\text{vol}\text{(H(x, ξ)?λ)}\text{∫}\text{H?λ}\text{f(a(x, ξ))dxdξ}$

(assuming one limit exists).     

Almost sure central limit theorems for random functions

Let {Xn,-∞< n <∞} be a sequence of independent identically distributed random variables with EX1 = 0, EX12 = 1 and let Sn =∑k=1∞Xk, and Tn = Tn(X1,…,Xn) be a random function such that Tn = ASn Rn, where supn E|Rn| <∞and Rn = o(n~(1/2)) a.s., or Rn = O(n1/2-2γ) a.s., 0 <γ< 1/8. In this paper, we prove the almost sure central limit theorem (ASCLT) and the function-typed almost sure central limit theorem (FASCLT) for the random function Tn. As a consequence, it can be shown that ASCLT and FASCLT also hold for U-statistics, Von-Mises statistics, linear processes, moving average processes, error variance estimates in linear models, power sums, product-limit estimators of a continuous distribution, product-limit estimators of a quantile function, etc.     

Some scaled limit theorems for an immigration super-Brownian motion

In this paper,the small time limit behaviors for an immigration super-Brownian motion are studied,where the immigration is determined by Lebesgue measure.We first prove a functional central limit theorem,and then study the large and moderate deviations associated with this central tendency.     

Functional limit theorems for the “disorder” problem

Let X ⁽ⁿ⁾=(X _k ), 1≦k≦n be random process with discrete time defined by its transition probabilities which belong to some parametric family. It is assumed that the parameters of the transition probabilities before and/or after disorder as well as the disorder time, are unknown. For statistical purposes the processes of Radon-Nikodym derivatives of the measures generated by processes with disorder at the time s with respect to the measure generated by process without disorder where 1≦s≦n are often used. In the paper general sufficient conditions are given for weak convergence of these processes. Some examples are given to illustrate the application of the results obtained.     

Strong limit theorems for anisotropic random walks on ℤ2

We study the path behaviour of the anisotropic random walk on the two-dimensional lattice ?². Strong approximation of its components with independent Wiener processes is proved. We also give some asymptotic results for the local time in the periodic case.     

On the necessity of Statulevičius' condition in limit theorems for large-deviation probabilities

For a sequence of independent identically distributed random variables with zero mean and unit variance, the problem of necessity of Statulevičius' condition in limit theorems for large-deviation probabilities is investigated. St. Petersburg State Technical University. Translated from Lietuvos Matematikos Rinkinys, Vol. 39, No. 3, pp. 293–303, July–September, 1999. Translated by N. N. Amosova     

Hermite–Hadamard inequality for convex stochastic processes

In this note we extend the classical Hermite–Hadamard inequality to convex stochastic processes.     

Asymptotic expansions for partial solutions of the sixth Painlevé equation

A formalism for an averaging method for the Painlevé equations, in particular, the sixth equation, is developed. The problem is to describe the asymptotic behavior of the sixth Painlevé transcendental in the case where the module of the independent variable tends to infinity. The corresponding expansions contain an elliptic function (ansatz) in the principal term. The parameters of this function depend on the variable because of the modulation equation. The elliptic ansatz and the modulation equation for the sixth Painlevé equation are obtained in their explicit form. A partial solution of the modulation equation leading to a previously unknown asymptotic expansion for the partial solution of the sixth Painlevé equation is obtained.     

Asymptotic preserving schemes for the Klein–Gordon equation in the non-relativistic limit regime

We consider the Klein–Gordon equation in the non-relativistic limit regime, i.e. the speed of light $c$ tending to infinity. We construct an asymptotic expansion for the solution with respect to the small parameter depending on the inverse of the square of the speed of light. As the first terms of this asymptotic can easily be simulated our approach allows us to construct numerical algorithms that are robust with respect to the large parameter $c$ producing high oscillations in the exact solution.     

Functional central limit theorem for super α-stable processes

A functional central limit theorem is proved for the centered occupation time process of the super α-stable processes in the finite dimensional distribution sense. For the intermediate dimensions α < d < 2α. (0 < α ≤ 2), the limiting process is a Gaussian process, whose covariance is specified; for the critical dimension d = 2α and higher dimensions d > 2α, the limiting process is Brownian motion.     

Functional central limit theorem for super α-stable processes

A functional central limit theorem is proved for the centered occupation time process of the super α-stable processes in the finite dimensional distribution sense. For the intermediate dimensions α < d < 2α (0 < α ≤ 2), the limiting process is a Gaussian process, whose covariance is specified; for the critical dimension d= 2α and higher dimensions d < 2α, the limiting process is Brownian motion. Zhang Mei, Functional central limit theorem for the super-brownian motion with super-Brownian immigration, J. Theoret. Probab., to appear.     

Asymptotic expansions and convergence rates for Euler’s approximations of semigroups

We provide optimal bounds for errors in Euler’s approximations of semigroups in Banach algebras and of semigroups of operators in Banach spaces. Furthermore, we construct asymptotic expansions for such approximations with optimal bounds for remainder terms. The sizes of errors are controlled by smoothness properties of semigroups. In this paper we use Fourier–Laplace transforms and a reduction of the problem to the convergence rates and asymptotic expansions in the Law of Large Numbers. The research was partially supported by the Lithuanian State Science and Studies Foundation, grant No. T-70/09. This paper was written in 2004. In the interim, several related articles were published; let us mention [14, 13, 15].     

Nonlinear stochastic integrals for hyperfinite Lévy processes

I develop a notion of nonlinear stochastic integrals for hyperfinite Lévy processes and use it to find exact formulas for expressions which are intuitively of the form and , where l is a Lévy process. These formulas are then applied to geometric Lévy processes, infinitesimal transformations of hyperfinite Lévy processes, and to minimal martingale measures. Some of the central concepts and results are closely related to those found in S. Cohen’s work on stochastic calculus for processes with jumps on manifolds, and the paper may be regarded as a reworking of his ideas in a different setting and with totally different techniques.     

Asymptotic sampling – a tool for efficient reliability computation in high dimensions

Monte Carlo methods are most versatile regarding applications to the reliability analysis of high-dimensional nonlinear structural systems. In addition to its versatility, the computational efficacy of Monte Carlo method is not adversely affected by the dimensionality of the problem. Crude Monte Carlo techniques, however, are very inefficient for extremely small failure probabilities such as typically required for sensitive structural systems. Therefore methods to increase the efficacy for small failure probability while keeping the adverse influence of dimensionality small are desirable. On such method is the asymptotic sampling method. Within the framework of this method, well-known asymptotic properties of the reliability index regarding the scaling of the basic variables are exploited to construct a regression model which allows to determine the reliability index for extremely small failure probabilities with high precision using a moderate number of Monte Carlo samples. (© 2015 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim)     

Asymptotic results for finite superpositions of Ornstein–Uhlenbeck processes

A model of intermittency based on superposition of Lévy driven Ornstein–Uhlenbeck processes is studied in [6 Grahovac, D., Leonenko, N., Sikorskii, A., and Te?niak, I. 2016. Intermittency of superpositions of Ornstein–Uhlenbeck type processes. J. Stat. Phys. 165:390–408.[Crossref], [Web of Science ®] , [Google Scholar]]. In particular, as shown in Theorem 5.1 in that paper, finite superpositions obey a (sample path) central limit theorem under suitable hypotheses. In this paper we prove large (and moderate) deviation results associated with this central limit theorem.     

Asymptotic results for exponential functionals of Lévy processes

The asymptotic behavior of expectations of some exponential functionals of a Lévy process is studied. The key point is the observation that the asymptotics only depend on the sample paths with slowly decreasing local infimum. We give not only the convergence rate but also the expression of the limiting coefficient. The latter is given in terms of some transformations of the Lévy process based on its renewal function. As an application, we give an exact evaluation of the decay rate of the survival probability of a continuous-state branching process in random environment with stable branching mechanism.