An estimate of the remainder term in the central limit theorem for r-independent random variables

We suggest a method for the investigation ofr-independent random variables by using multiplicative systems. An estimate of the remainder term in the central limit theorem forr-independent random variables is obtained.Translated from Ukrainskii Matematicheskii Zhurnal, Vol. 45, No. 5, pp. 725–727, May, 1993.     

关于图值随机元序列的强极限定理

本文研究在局部连通图中取值的随机元的r-阶均值集、r-阶广义样本均值集的基本性质及其极限性质.利用关于随机元的分离引理以及随机游动的常返性,得到了关于图值随机元序列广义强大数定理.推广了已有的结果.     

On a sequential model of the algebra of finite-valued logic

We consider basic postulates for an interpretation of the algebra of finite-valued logic in which prepositional variables are interpreted as variables whose values are sequences. We obtain an analytic representation of the operations of two-valued logic for a class of recursive sequences—generalized arithmetic progressions. We exhibit certain generalizations, modifications, and applications of the proposed model.Translated fromMatematicheskie Metody i Fiziko-Mekhanicheskie Polya, Issue 32, 1990, pp. 14–17.     

Sooner and Later Waiting Time Problems Based on a Dependent Sequence

This paper introduces a new concept: a binary sequence of order (k,r), which is an extension of a binary sequence of order k and a Markov dependent sequence. The probability functions of the sooner and later waiting time random variables are derived in the binary sequence of order (k,r). The probability generating functions of the sooner and later waiting time distributions are also obtained. Extensions of these results to binary sequence of order (g,h) are also presented.     

Set estimation under convexity type assumptions

The problem of estimating a set S from a random sample of points taken within S is considered. It is assumed that S is r-convex, which means that a ball of radius r can go around from outside the set boundary. Under this assumption, the r-convex hull of the sample is a natural estimator of S. We obtain convergence rates for this estimator under both the distance in measure and the Hausdorff metric between sets. It is also proved that the boundary of the estimator consistently estimates the boundary of S, in Hausdorff's sense.     

Invariance and independence in multivariate distribution theory

Several general results are presented whereby various properties of independence or conditional independence between certain random variables may be deduced from the symmetries enjoyed by their joint distributions. These are applied to the distributions of sample correlation and canonical correlation coefficients when the underlying data-distribution has suitable orthogonal invariance. A typical result is that, for a random sample of observations on three independent normal variables, r₁₂, r₁₃, and r_23.1 are mutually independent.     

行m-NSD随机变量阵列的完全收敛性

本文研究了行m-NSD随机变量阵列的完全收敛性问题.主要利用m-NSD随机变量的Kolmogorov型指数不等式,获得了行m-NSD随机变量阵列的完全收敛性定理,将Hu等（1998）andSung等（2005）的结果从独立情形推广到了m-NSD随机变量阵列.本文的结论同样推广了Chen等（2008）,Hu等（2009）,Qiu等（2011）和Wang等（2014）的结果.     

Remarks on the r and Δ convolutions

In this paper we study the properties of the r–deformation introduced in [B1]. We observe that the associated convolution coming from the conditionally free convolution is associative only for r = 1 and r = 0. We give the realization of some r–Gaussian random variables and obtain Haagerup–Pisier–Buchholz type inequalities. We also study another convolution defined with the use of the r–deformation through a moment–cumulant formula [KY1] and show that it is associative and in general not positive. Partially sponsored with KBN grant no 2P03A00723 and RTN HPRN-CT-2002-00279.     

Derivation of the probability distribution functions for succession quota random variables

The probability distribution functions (pdf's) of the sooner and later waiting time random variables (rv's) for the succession quota problem (k successes and r failures) are derived presently in the case of a binary sequence of order k. The probability generating functions (pgf's) of the above rv's are then obtained directly from their pdf's. In the case of independent Bernoulli trials, expressions for the pdf's in terms of binomial coefficients are also established.     

Mean Convergence Theorems for Weighted Sums of Arrays of Residually <Emphasis Type="Italic">h</Emphasis>-integrable Random Variables Concerning the Weights under Dependence Assumptions

From the classical notion of uniform integrability of a sequence of random variables, a new concept called residual h-integrability is introduced for an array of random variables, concerning an array of constants, which is weaker than other previous related notions of integrability. Martingale difference, pairwise negative quadrant dependence, tail φ-mixing property and L _p -mixingale are four special kinds of dependence structures, where 1≤p≤2. By relating the residual h-integrability with such these dependence assumptions, some conditions are formulated under which mean convergence theorems for weighted sums of arrays of random variables are established, and many earlier results are explained as the special cases of the ones appearing in our present work.      

LIL and the Approximation of Rectangular Sums of B-valued Random Variables when Extreme Terms are Excluded

Let be a field of i.i.d. random variables indexed by d-tuples of positive integers and taking values in a Banach space ℬ and let if is the r-th maximum of . Let and . We approximate the trimmed sums by a Brownian sheet and obtain sufficient and necessary conditions for to satisfy the compact and functional laws of the iterated logarithm. These results improve the previous works by Morrow (1981), Li and Wu (1989) and Ledoux and Talagrand (1990). Received March 22, 1999, Accepted October 13, 2000     

E -Theoretic Duality for Higher Rank Graph Algebras

We prove that there is a Poincaré type duality in E-theory between higher rank graph algebras associated with a higher rank graph and its opposite correspondent. We obtain an r-duality, that is the fundamental classes are in E^r. The basic tools are a higher rank Fock space and higher rank Toeplitz algebra which has a more interesting ideal structure than in the rank 1 case. The K-homology fundamental class is given by an r-fold exact sequence whereas the K-theory fundamental class is given by a homomorphism. The E-theoretic products are essentially pull-backs so that the computation is done at the level of exact sequences. Mathematics Subject Classification (2000): 46L80.     

On the rate of approximation in the central limit theorem for dependent random variables and random vectors

Large “O” and small “o” approximations of the expected value of a class of smooth functions (f C^r(R)) of the normalized partial sums of dependent random variable by the expectation of the corresponding functions of normal random variables have been established. The same types of approximations are also obtained for dependent random vectors. The technique used is the Lindberg-Levy method generalized by Dvoretzky to dependent random variables.     

A General Upper Bound for the Satisfiability Threshold of Randomr-SAT Formulae

Experiments on solvingr-SAT random formulae have provided evidence of a satisfiability threshold phenomenon with respect to the ratio of the number of clauses to the number of variables of formulae. Presently, only the threshold of 2-SAT formulae has been proved to exist and has been computed to be equal to 1. For 3-SAT formulae and more generally forr-SAT formulae, lower and upper bounds of the threshold have been established. The best established bounds concern 3-SAT. For an observed threshold of about 4.25, the best lower bound is 3.003 and the best upper bound 4.76. In this paper we establish a general upper bound of the threshold forr-SAT formulae giving a value for 3-SAT of 4.64, significantly improving the previous best upper bound. For this we have defined a more restrictive structure than a satisfying truth assignment for characterizing the satisfiability of a SAT formula which we have called negatively prime solution (NPS). By merely applying the first moment method to negatively prime solutions of a randomr-SAT formula we obtain our bound.     

Numerical Computation of Multivariate Normal and Multivariate-t Probabilities over Convex Regions

Abstract

A methodology has been developed and Fortran 90 programs have been written to evaluate multivariate normal and multivariate-t integrals over convex regions. The Cholesky transformation is used to transform the integrand into a product of standard normal or spherically symmetric t variables. For any random direction from the origin, an unbiased estimate of the value of the integral is Pr[X ² ≥ r²] (multivariate normal) or Pr[F ≥ r²/k] (multivariate-t), where r is the distance from the origin to the boundary in a randomly chosen direction, and k is the dimension of the integral. Two Fortran 90 programs have been written. MVI uses the average of many estimates. MVIB uses a binning procedure to obtain an empirical distribution of the distance from the origin to the boundary. Gauss-Legendre quadrature is then used to estimate the value of the integral. The running time for MVIB is modestly smaller than that for MVI. However, in solving certain integral equations (e.g., using an iterative procedure to find the percentage point of a statistic), using MVIB usually requires no Monte Carlo sampling after the first iteration, and is considerably more efficient. MVIB and MVI are highly efficient for the evaluation of integrals whose value is large. “Naive” Monte Carlo (MC) may be competitive with MVI or MVIB only if the value of the probability integral is small or the shape of the region is “extreme.”     

Resultants and contour integrals

Resultants are important special functions used to describe nonlinear phenomena. The resultant R_{r1 ?rn} R_{r_1 \ldots r_n } determines a consistency condition for a system of n homogeneous polynomials of degrees r ₁, ..., r _n in n variables in precisely the same way as the determinant does for a system of linear equations. Unfortunately, there is a lack of convenient formulas for resultants in the case of a large number of variables. In this paper we use Cauchy contour integrals to obtain a polynomial formula for resultants, which is expected to be useful in applications.     

Limit distribution of the number of consecutive records

A succinct series expression is derived for describing the limit distribution of the number of times r consecutive elements are all records (in a sequence of independent and identically distributed random variables with a common continuous distribution) for all r ≥ 2. Previously, only the limit distributions for r = 1, 2, and 3 were known. © 2005 Wiley Periodicals, Inc. Random Struct. Alg., 2005     

Truncated stable random variables: characterization and simulation

Kanter (Ann Probab 3(4):697–707, 1975) and Chambers et al. (J Am Stat Assoc 71(354):340–344, 1976) developed a method for characterizing and simulating stable random variables, X, using nonlinear transformations involving two independent uniform random variables. Their method is scrutinized to provide a characterization and then develop a method for simulating random variables with distribution P(X ≤ x| X  > a), called here truncated stable random variables. Our characterization is rigorous when the characteristic exponent α ≠ 1. We extend our method to the case that α → 1.     

A Lower Bound of <Emphasis Type="Italic">L</Emphasis><Subscript><Emphasis Type="Italic">p</Emphasis></Subscript> Norms in the CLT for Strongly Mixing Random Variables

We derive a lower bound of L _p norms, 1 ⩽ p ⩽ ∞, in the central limit theorem for strongly mixing random variables X ₁,..., X _n with under the boundedness condition ℙ{|X _i | ⩽ M} = 1 with a nonrandom constantM > 0 and condition ∑ _r⩾1 r ²α(r) < ∞, where α(r) are the Rosenblatt strong mixing coefficients. __________ Translated from Lietuvos Matematikos Rinkinys, Vol. 45, No. 4, pp. 587–602, October–December, 2005.