A semigroup characterization of the multiparameter Wiener process

It is well known that the infinitesimal operator characterizes the Wiener process {W(t), t≥0}. In this paper we show that the family of operators plays the same role for the q-parameter Wiener process. Partially supported by CNPq Grant No. 200. 607/82.     

A Wiener test for integrals of brownian motion and the existence of smooth curves in nowhere dense sets

Let J_ω^x(t) = x + ∝₀^tb_ω(s) ds, where b_ω is planar Brownian motion starting at 0. A Wiener-type criterion is proved for the process J_ω^x(t): Let K be a compact plane set and let x?K. Then if ∑ 2ⁿM₁(A_n(x)?K) < ∞ (where $\text{A}{}_{\mathrm{n}}\text{(x) = {2}{}^{\mathrm{?n?1}}\text{? ¦ z ? x ¦ ? 2}{}^{\mathrm{?n}}\text{}}$ and M₁ denotes one-dimensional Hausdorff content), the process J_ω^x(t) stays within K for a positive period of time t, a.s. In particular, this applies to almost all x with respect to area in the nowhere dense “Swiss Cheese” sets. The method is based on general potential theory for Markov processes.     

Stochastic integrals for nonprevisible,multiparameter processes

We develop a general theory for stochastic integrals of generalized stochastic processesX(t), depending on multidimensional time, within the framework of the space of Wiener distributions (D ^*).     

Necessary conditions for renewal processes approximating to Wiener processes

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Laws of the iterated logarithm for iterated Wiener processes

The recent interest in iterated Wiener processes was motivated by apparently quite unrelated studies in probability theory and mathematical statistics. Laws of the iterated logarithm (LIL) were independently obtained by Burdzy⁽²⁾ and Révész⁽¹⁷⁾. In this work, we present a functional version of LIL for a standard iterated Wiener process, in the spirit of functional asymptotic results of an ²-valued Gaussian process given by Deheuvels and Mason⁽⁹⁾ in view of Bahadur-Kiefer-type theorems. Chung's liminf sup LIL is established as well, thus providing further insight into the asymptotic behavior of iterated Wiener processes.     

Uniform packing dimension results for multiparameter stable processes

In this article, authors discuss the problem of uniform packing dimension of the image set of multiparameter stochastic processes without random uniform H(o)lder condition, and obtain the uniform packing dimension of multiparameter stable processes.If Z is a stable (N, d, α)-process and αN ≤ d, then the following holds with probability 1 Dim Z(E) = α DimE for any Borel setE ∈ B(R N),where Z(E) = {x: (E) t ∈ E, Z(t) = x}. Dim(E) denotes the packing dimension of E.     

Absolute continuity of Wiener processes

By a Wiener process we mean a countably additive random measure taking independent values on disjoint sets. Given two continuous Wiener processes we give their decomposition into weakly equivalent and mutually singular parts.     

Occupation densities for stochastic integral processes in the second Wiener chaos

Summary The two-point distributions of Skorohod integral processes in the second Wiener chaos are mainly described by a Hilbert-Schmidt operatorT giving the mutual interaction of infinitely many Gaussian components and by simple multiplication operators. So are the Fourier transforms of their occupation measures. This enables us to use the well known Fourier analytic criterion discovered and elaborated by Berman to derive integral conditions for the existence of their occupation densities in terms of associated Hilbert-Schmidt operators. IfT is a trace class operator, we get a necessary and sufficient criterion, if it is not, still a sufficient one. In a case in which the interaction is particularly simple, we verify the appropriate integral condition and show that the results are essentially beyond the reach of enlargement of filtrations techniques of semimartingale theory.     

The strong Markov property for canonical Wiener processes

A noncommutative analog of the concept of Markov time is formulated, in association with a canonical Wiener process (P, Q) [4]. For such a Markov time T, the quantities P_T(t) = P(t + T) ? P(T), Q_T(t) = Q(t + T) ? Q(T) can be defined using spectral integrals with operator-valued integrands, and constitute a new canonical Wiener process (P_T, Q_T), which is independent of the analog of the σ-field of events generated by the process up to the Markov time.     

Binary terms in polynomial representations of Boolean functions

Polynomial representations of Boolean functions by binary terms are considered. The construction of terms involves variables and residual functions. Special cases of such representations are the decomposition of a function with respect to variables, Zhegalkin polynomials, and representations of functions as sums of conjunctions of residual functions.     

A test for the existence of exceptional points in the Faddeev scattering problem

Exceptional points are values of the spectral parameter for which the homogeneous Faddeev scattering problem has a nontrivial solution. We formulate a criterion for existence of exceptional points that belong to a given path. For this, we use measurements at the endpoints of the path. We also study the existence or absence of exceptional points for small perturbations of conductive potentials of arbitrary shape and show that problems with absorbing potentials do not have exceptional points in a neighborhood of the origin.     

Wiener processes with random effects for degradation data

This article studies the maximum likelihood inference on a class of Wiener processes with random effects for degradation data. Degradation data are special case of functional data with monotone trend. The setting for degradation data is one on which n independent subjects, each with a Wiener process with random drift and diffusion parameters, are observed at possible different times. Unit-to-unit variability is incorporated into the model by these random effects. EM algorithm is used to obtain the maximum likelihood estimators of the unknown parameters. Asymptotic properties such as consistency and convergence rate are established. Bootstrap method is used for assessing the uncertainties of the estimators. Simulations are used to validate the method. The model is fitted to bridge beam data and corresponding goodness-of-fit tests are carried out. Failure time distributions in terms of degradation level passages are calculated and illustrated.     

The generalized Wiener Theorem for groups with finite dimensional irreducible representations

It is shown that the generalized Wiener Theorem for ideals in group algebras of locally compact Abelian groups extends to group algebras of locally compact groups with finite-dimensional irreducible representations (Moore groups).     

Markov properties of multiparameter processes and capacities

Summary We study a class of multiparameter symmetric Markov processes. We prove that this class is stable by subordination in Bochner's sense. We show then that for these processes, a probabilistic and an analytic potential theory correspond to each other. In particular, additive functionals are associated with finite energy measures, hitting probabilities are estimated by capacities, quasicontinuity corresponds to path-continuity. In the last section, examples show that many earlier results, as well as new ones, in this domain can be obtained by our method.     

An integral test for the supremum of Wiener local time

Summary The upper classes of the supremum of Wiener (Brownian) local time are characterized by convergence or divergence of a certain integral.Dedicated to Klaus Krickeberg on the occasion of his 60th birthdayResearch supported by Hungarian National Foundation for Scientific Research Grant No. 1808     

A test for the independence of two Gaussian processes

A bivariate Gaussian process with mean 0 and covariance

$\text{Σ(s, t, p)=}\text{Σ}{}_{11}\text{(s, t)}\text{ρΣ}{}_{12}\text{(s, t)}\text{ρΣ}{}_{21}\text{(s, t)}\text{Σ}{}_{22}\text{(s, t)}$

is observed in some region Ω of R′, where {Σ_ij(s,t)} are given functions and p an unknown parameter. A test of H₀: p = 0, locally equivalent to the likelihood ratio test, is given for the case when Ω consists of p points. An unbiased estimate of p is given. The case where Ω has positive (but finite) Lebesgue measure is treated by spreading the p points evenly over Ω and letting p → ∞. Two distinct cases arise, depending on whether Δ_2,p, the sum of squares of the canonical correlations associated with Σ(s, t, 1) on $\text{Ω}{}^2$, remains bounded. In the case of primary interest as p → ∞, Δ_2,p → ∞, in which case $\text{p}\text{?}$ converges to p and the power of the one-sided and two-sided tests of H₀ tends to 1. (For example, this case occurs when Σ_ij(s, t) ≡ Σ₁₁(s, t).)     

Laws of iterated logarithm of multiparameter wiener processes

Let {$\text{X(}\text{t}\text{) :}\text{t}\text{∈ R}{}_{\mathrm{+}}{}^{\mathrm{N}}$} denote the N-parameter Wiener process on $\text{R}{}_{\mathrm{+}}{}^{\mathrm{N}}\text{= [0, ∞)}{}^{\mathrm{n}}$. For multiple sequences of certain independent random variables the authors find lower bounds for the distributions of maximum of partial sums of these random variables, and as a consequence a useful upper bound for the yet unknown function , c ≥ 0, is obtained where D_N = Π_{k = 1}^N [0, T_k]. The latter bound is used to give three different varieties of N-parameter generalization of the classical law of iterated logarithm for the standard Brownian motion process.     

A convergence–divergence test for series of nonnegative terms

We present a convergence–divergence test for series of nonnegative terms. Our proof is elementary, and yet we show examples of application to some apparently difficult cases.