Random sieves,II

A proof is presented that the random sieve, a stochastic analogue of the sieve of Eratosthenes, generates sequences of numbers approximating the density of primes. The expected number E_n[h] of such numbers less than n satisfies

$\text{E}{}_{\mathrm{n}}\text{[h]/π(n)→1}$

and the actual number h(n), on any trial, approximates π(n) in the sense of the weak law of large numbers. Some additional results are given.     

Random Diophantine equations,I

We consider additive Diophantine equations of degree k in s   variables and establish that whenever s?3k+2$s?3k+2$ then almost all such equations satisfy the Hasse principle. The equations that are soluble form a set of positive density, and among the soluble ones almost all equations admit a small solution. Our bound for the smallest solution is nearly best possible.     

随机非线性凝聚算子方程的随机解

利用随机拓扑度理论研究随机非线性凝聚算子,在一定条件下得到随机算子方程A（w,x）=μx的随机解和随机算子不动点的存在性,所得结论减弱了已知文献中相应定理的条件．     

关于随机算子方程的随机解

本文研究了随机算子方程（Ａ（ω，ｘ）＝μｘ，（ω，ｘ）∈Ω×Ｄ，μ１）的随机解，得到了若干新的结果，同时，我们推广了著名的Ａｌｔｍａｎ定理．     

Random variables,monotone relations,and convex analysis

Random variables can be described by their cumulative distribution functions, a class of nondecreasing functions on the real line. Those functions can in turn be identified, after the possible vertical gaps in their graphs are filled in, with maximal monotone relations. Such relations are known to be the subdifferentials of convex functions. Analysis of these connections yields new insights. The generalized inversion operation between distribution functions and quantile functions corresponds to graphical inversion of monotone relations. In subdifferential terms, it corresponds to passing to conjugate convex functions under the Legendre–Fenchel transform. Among other things, this shows that convergence in distribution for sequences of random variables is equivalent to graphical convergence of the monotone relations and epigraphical convergence of the associated convex functions. Measures of risk that employ quantiles (VaR) and superquantiles (CVaR), either individually or in mixtures, are illuminated in this way. Formulas for their calculation are seen from a perspective that reveals how they were discovered. The approach leads further to developments in which the superquantiles for a given distribution are interpreted as the quantiles for an overlying “superdistribution.” In this way a generalization of Koenker–Basset error is derived which lays a foundation for superquantile regression as a higher-order extension of quantile regression.     

Curvature Measures and Random Sets,I

The paper deals with signed curvature measures as introduced by Federer for sets with positive reach. An integral representation and a local Steiner formula for these measures are given. The main result is the additive extension of the curvature measures to locally finite unions of compatible sets with positive reach. Within this comprehensive class of subsets of R^d a generalized Steiner polynomial (local version) and section theorems (principal kinematic formula, Crofton formula) for the curvature measures are derived.     

Random weighting,asymptotic counting,and inverse isoperimetry

For a family X of k-subsets of the set {1, …, n}, let |X| be the cardinality of X and let Γ(X, μ) be the expected maximum weight of a subset from X when the weights of 1, …, n are chosen independently at random from a symmetric probability distribution μ on ℝ. We consider the inverse isoperimetric problem of finding μ for which Γ(X, μ) gives the best estimate of ln |X|. We prove that the optimal choice of μ is the logistic distribution, in which case Γ(X, μ) provides an asymptotically tight estimate of ln |X| as k ⁻¹ ln |X} grows. Since in many important cases Γ(X, μ) can be easily computed, we obtain computationally efficient approximation algorithms for a variety of counting problems. Given μ, we describe families X of a given cardinality with the minimum value of Γ(X, μ), thus extending and sharpening various isoperimetric inequalities in the Boolean cube. The research of the first author was partially supported by NSF Grants DMS 9734138 and DMS 0400617. The research of the second author was partially supported by ISF Grant 039-7165 and by GIF grant I-2052.     

Random walks,Kleinian groups,and bifurcation currents

Let (ρ _λ ) _λ∈Λ be a holomorphic family of representations of a finitely generated group G into PSL(2,ℂ), parameterized by a complex manifold Λ. We define a notion of bifurcation current in this context, that is, a positive closed current on Λ describing the bifurcations of this family of representations in a quantitative sense. It is the analogue of the bifurcation current introduced by DeMarco for holomorphic families of rational mappings on ℙ¹. Our definition relies on the theory of random products of matrices, so it depends on the choice of a probability measure μ on G.     

Matrix Measures, Random Moments, and Gaussian Ensembles

We consider the moment space M_n\mathcal{M}_{n} corresponding to p×p real or complex matrix measures defined on the interval [0,1]. The asymptotic properties of the first k components of a uniformly distributed vector (S_1,n, ... , S_n,n)^* ~ U (M_n)(S_{1,n}, \dots , S_{n,n})^{*} \sim\mathcal{U} (\mathcal{M}_{n}) are studied as n→∞. In particular, it is shown that an appropriately centered and standardized version of the vector (S _1,n ,…,S _k,n )^∗ converges weakly to a vector of k independent p×p Gaussian ensembles. For the proof of our results, we use some new relations between ordinary moments and canonical moments of matrix measures which are of their own interest. In particular, it is shown that the first k canonical moments corresponding to the uniform distribution on the real or complex moment space M_n\mathcal{M}_{n} are independent multivariate Beta-distributed random variables and that each of these random variables converges in distribution (as the parameters converge to infinity) to the Gaussian orthogonal ensemble or to the Gaussian unitary ensemble, respectively.     

Riesz Products, Random Walks, and the Spectrum

It is shown that to a classical Riesz product one can naturally assign a random walk; the spectrum of the shifts on the tail algebra of the random walk is defined by the measure to which the Riesz product converges. This observation is extended to general groups, which leads to some operator analogs of Riesz products. The properties of operator Riesz products are investigated.     

Prophet Regions for Independent [0, 1]-Valued Random Variables with Random Discounting

Abstract

Let X ₁, X ₂… and B ₁, B ₂… be mutually independent [0, 1]-valued random variables, with EB _j  = β > 0 for all j. Let Y _j  = B ₁ … sB _j?1 X _j for j ≥ 1. A complete comparison is made between the optimal stopping value V(Y ₁,…,Y _n ):=sup{EY _τ:τ is a stopping rule for Y ₁,…,Y _n } and E(max _1≤j≤n Y _j ). It is shown that the set of ordered pairs {(x, y):x = V(Y ₁,…,Y _n ), y = E(max _1≤j≤n Y _j ) for some sequence Y ₁,…,Y _n obtained as described} is precisely the set {(x, y):0 ≤ x ≤ 1, x ≤ y ≤ Ψ _{n, β}(x)}, where Ψ _{n, β}(x) = [(1 ? β)n + 2β]x ? β^?(n?2) x ² if x ≤ β ^n?1, and Ψ _{n, β}(x) = min _j≥1{(1 ? β)jx + β ^j } otherwise. Sharp difference and ratio prophet inequalities are derived from this result, and an analogous comparison for infinite sequences is obtained.     

随机模糊集与随机集

本文研究了三个方面的工作：一是定义了一种模糊集上的可测结构，从而定义了随机模糊集，这些定义都与论域Ｘ上的拓扑结构无关。将通常意义下的集合看成特殊模糊集得到的通常集合上的超可测结构与文（３）中的定义一致；二是给出了随机模糊集、随机集的一些等价条件；三是研究了随机模糊集、随机集的分布与其有限维落影族的关系。     

可交换随机变量序列的随机极限定理

本文讨论了可交换随机变量序列{X_n:n≥1}的极限定理,得到了可交换随机变量序列的随机强大数律及加权和定理,并推广了文[4]中的结果.     

一类随机环境中的随机游动

在Solomn的模型的基础上对一类随机环境中随机游动进行了讨论，并得出了一个常返性准则和一些极限性质。     

一类随机环境中的随机游动

研究了在环境平稳遍历时,右半直线上可逗留的随机环境中的随机游动的常返性和非常返性,给出非常返、正常返、零常返的充要条件,并讨论了极限性质.作为推论,给出P独立同分布时的相应结论.