Unbiased estimation for negative-binomial random walks

Unbiased estimates are proposed for some functions of parameters of distributions generated by negative-binomial random walks. Translated fromStatisticheskie Metody Otsenivaniya i Proverki Gipotez, pp. 18–20, Perm, 1990.     

Increasing permutations of random processes

The paper is concerned with an application of limit theorems to the study of increasing permutations of stable random processes. By the increasing permutation of a function is meant the nondecreasing function with the same distribution. The trajectories of a random process may be approximated by step-functions, and then the continuity of the increasing permutation operator permits one to apply the Skorokhod invariance principle to obtain the distribution of the random process. The distribution function and the expected value of the increasing permutation of a stable random process are given explicitly. Also the univariate distributions of the increasing permutation of the Cauchy process are obtained. In various normed spaces the images of the unit balls with respect to the operator of increasing permutation are described. A separate section is devoted to the increasing permutations of higher-dimensional processes. Bibliography: 5 titles. Translated fromZapiski Nauchnykh Seminarov POMI, Vol. 216, 1994, pp. 62–75. Translated by A. Sudakov.     

Inequalities for moments of symmetric polynomial forms in random variables

In the last few years, interest in the properties of distributions of quadratic and polynomial forms in random variables has again grown. Translated fromStatisticheskie Metody Otsenivaniya i Proverki Gipotez, pp. 159–161, Perm, 1993.     

Uniform in dimension estimates of the scatter of distributions of Gaussian random functionals for some classes of multivariate measures

We establish uniform in dimension estimates of the scatter of distributions of linear functionals chosen at random with respect to the Gaussian distribution for uniform discrete distributions and for Gaussian distributions on a vector space. Bibliography: 5 titles.Translated from Zapiski Nauchnykh Seminarov POMI, Vol. 294, 2002, pp. 194–199.This research was supported by the Russian Foundation for Basic Research, grants 99-15-96019, 02-01-00263, and 99-01-04027.Translated by V. N. Sudakov.     

Coherent random allocations, and the Ewens-Pitman formula

Assume that there is a random number K of positive integer random variables S₁, …, S_K that are conditionally independent given K and all have identical distributions. A random integer partition N = S₁ + S₂ + … + S_K arises, and we denote by P_N the conditional distribution of this partition for a fixed value of N. We prove that the distributions {P_N} _N=1 ^∞ form a partition structure in the sense of Kingman if and only if they are governed by the Ewens-Pitman Formula. The latter generalizes the celebrated Ewens sampling formula, which has numerous applications in pure and applied mathematics. The distributions of the random variables K and S_j belong to a family of integer distributions with two real parameters, which we call quasi-binomial. Hence every Ewens-Pitman distribution arises as a result of a two-stage random procedure based on this simple class of integer distributions. Bibliography: 25 titles. This paper is an edited and actualized version of the unpublished PDMI preprint 21/1995. Further development of the ideas of this work can be found in [21, 25]. A number of detected misprints was fixed without notice, the bibliography was extended beyond the original 19 references, and a few comments were added as footnotes. (Comments by Alexander Gnedin.) __________ Translated from Zapiski Nauchnykh Seminarov POMI, Vol. 325, 2005, pp. 127–145.     

Limiting distributions and estimation in generalized Polya random walk scheme

Asymptotic behavior of distributions generated by Polya random walks is investigated. Unbiased estimators of these distributions are constructed for closed first-arrival plans.Translated from Statisticheskie Metody Otsenivaniya i Proverki Gipotez, pp. 20–36, 1986.     

The Esseen inequality for sums of a random number of differently distributed random variables

The problem of estimation of deviation of the distribution of the sum of a random number of differently distributed random variables from the normal distribution is considered, i.e., the Esseen inequality for distributions of random sums is established. As a particular case, the Berry-Esseen inequality is obtained.Translated from Matematicheskie Zametki, Vol. 22, No. 1, pp. 143–146, July, 1977.     

Asymptotical behavior of the variance of sums of random variables with random replacements

In this paper, we introduce a scheme of summation of independent random variables with random replacements. We consider a series of double arrays of identically distributed random variables that are row-wise independent, but such that neighboring rows contain a random common part of the repeating terms. By this-scheme we bscribe a model of strongly dependent noise. To investigate the sample mean of this noise, we consider the sum of random variables over the whole double array and its conditional variance with respect to replacements. For columns of the arrays we prove a covariance inequality. As a corollary of it, we demonstrate the law of large numbers for conditional variances. Bibliography: 4 titles. Translated fromZapiski Nauchnykh Seminarov POMI, Vol. 216, 1994, pp. 124–143. Translated by A. Sudakov.     

Iterated probability distributions and extremes with random sample size

In this paper the possible nondegenerated limit distributions for the n-fold mapping of a given probability distribution are considered. If the mapping used for the iteration procedure is a probability generating function of a positive integer-valued random variable then the results can be applied to the max-stability of distributions of random variables with random sample size.     

A representation of strong Gaussian random operators

An integral representation of Gaussian random operators acting on a real separable Hilbert space is considered. In terms of this representation, boundedness conditions for Gaussian random operators are given. A special class of Gaussian random operators is studied.Translated from Teoriya Sluchainykh Protsessov, No. 16, pp. 19–23, 1988.     

A note on the sum of uniform random variables

An inductive procedure is used to obtain distributions and probability densities for the sum S_n of independent, non-equally uniform random variables. Some known results are then shown to follow immediately as special cases. Under the assumption of equally uniform random variables some new formulas are obtained for probabilities and means related to S_n. Finally, some new recursive formulas involving distributions are derived.     

Asymptotic behavior of the first arrival time in Markovian random walks

The article examines the asymptotic behavior of the first arrival time for homogeneous Markov random walks with a fixed stopping boundary. Conditions of convergence to exponential and gamma distributions are established. The results are applied to solve one problem of statistical control.Translated from Statisticheskie Metody, pp. 183–189, 1982.     

A family of random trees with random edge lengths

We introduce a family of probability distributions on the space of trees with I labeled vertices and possibly extra unlabeled vertices of degree 3, whose edges have positive real lengths. Formulas for distributions of quantities such as degree sequence, shape, and total length are derived. An interpretation is given in terms of sampling from the inhomogeneous continuum random tree of Aldous and Pitman (1998). ©1999 John Wiley & Sons, Inc. Random Struct. Alg., 15, 176–195, 1999     

Two-boundary problems for a random walk

We solve main two-boundary problems for a random walk. The generating function of the joint distribution of the first exit time of a random walk from an interval and the value of the overshoot of the random walk over the boundary at exit time is determined. We also determine the generating function of the joint distribution of the first entrance time of a random walk to an interval and the value of the random walk at this time. The distributions of the supremum, infimum, and value of a random walk and the number of upward and downward crossings of an interval by a random walk are determined on a geometrically distributed time interval. We give examples of application of obtained results to a random walk with one-sided exponentially distributed jumps. __________ Translated from Ukrains’kyi Matematychnyi Zhurnal, Vol. 59, No. 11, pp. 1485–1509, November, 2007.     

The phase transition in inhomogeneous random graphs

The “classical” random graph models, in particular G(n,p), are “homogeneous,” in the sense that the degrees (for example) tend to be concentrated around a typical value. Many graphs arising in the real world do not have this property, having, for example, power‐law degree distributions. Thus there has been a lot of recent interest in defining and studying “inhomogeneous” random graph models. One of the most studied properties of these new models is their “robustness”, or, equivalently, the “phase transition” as an edge density parameter is varied. For G(n,p), p = c/n, the phase transition at c = 1 has been a central topic in the study of random graphs for well over 40 years. Many of the new inhomogeneous models are rather complicated; although there are exceptions, in most cases precise questions such as determining exactly the critical point of the phase transition are approachable only when there is independence between the edges. Fortunately, some models studied have this property already, and others can be approximated by models with independence. Here we introduce a very general model of an inhomogeneous random graph with (conditional) independence between the edges, which scales so that the number of edges is linear in the number of vertices. This scaling corresponds to the p = c/n scaling for G(n,p) used to study the phase transition; also, it seems to be a property of many large real‐world graphs. Our model includes as special cases many models previously studied. We show that, under one very weak assumption (that the expected number of edges is “what it should be”), many properties of the model can be determined, in particular the critical point of the phase transition, and the size of the giant component above the transition. We do this by relating our random graphs to branching processes, which are much easier to analyze. We also consider other properties of the model, showing, for example, that when there is a giant component, it is “stable”: for a typical random graph, no matter how we add or delete o(n) edges, the size of the giant component does not change by more than o(n). © 2007 Wiley Periodicals, Inc. Random Struct. Alg., 31, 3–122, 2007     

On convergence to the poisson law for distributions of the sum of random variables connected into a chain

This paper deals with the triangular array of random variables where every sequence is connected into a stationary Markov chain. For the uniformly strongly mixing chain we find conditions under which the distributions of the sum converge to the Poisson law. A more general case of theL ^p-regular Markov chain is also considered. Institute of Mathematics and Informatics, Akademijos 4, 2600 Vilnius, Lithuania. Translated from Lietuvos Matematikos Rinkinys, Vol. 35, No. 3, pp. 297–307, July–September, 1995. Translated by R. Lapinskas     

Asymptotic normality of spherical means of nonlinear functionals of Gaussian random fields

The central limit theorem is proved for the integral-type functionals of nonlinear transformations of two-and three-dimensional uniform isotropic Gaussian random fields. A theorem on convergence of finite-dimensional distributions of these functionals to the corresponding distributions of the Wiener process is also established.Translated from Ukrainskii Matematicheskii Zhurnal, Vol. 45, No. 4, pp. 472–480, April, 1993.     

Criteria for testing nonparametric hypotheses for random processes

A criterion is constructed for testing the hypothesis on the homogeneity of the distributions of two random processes and some other hypotheses, consistent in a large class of alternatives.Translated from Zapiski Nauchnykh Seminarov Leningradskogo Otdeleniya Matematicheskogo Instituta im. V. A. Steklova Akademii Nauk SSSR, Vol. 184, pp. 8–13, 1990.     

On weak convergence of random fields

We provide a characterization of compactness in the spaceD of functions of two variables defined on a unit square. The functions fromD have the property that their discontinuity points lie on smooth curves. Conditions for the tightness of probability measures inD and conditions for weak convergence of random fields with trajectories inD are derived. Vilnius Gediminas Technical University, Saulétekio 11; Institute of Mathematics and Informatics, Akademijos 4, 2600 Vilnius, Lithuania. Translated from Lietuvos Matematikos Rinkinys, Vol. 39, No. 2, pp 169–184, April–June, 1999. Translated by R. Banys