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Uniform distribution and Voronoĭ convergence
Sbornik: Mathematics, 2005Udgivelsesdato: SEP ...
Kozlov, V.V., Madsen, Tatiana Kozlova
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2012
This chapter addresses central limit theorems, invariance principles and then proceeds to the convergence of empirical processes. The pathway will be to start with versions based on stationary variables and drop this assumption introducing the necessary control on the covariance structure.
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This chapter addresses central limit theorems, invariance principles and then proceeds to the convergence of empirical processes. The pathway will be to start with versions based on stationary variables and drop this assumption introducing the necessary control on the covariance structure.
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A metrization of class-convergences of distributions
Annals of the Institute of Statistical Mathematics, 1953Étant donnée une fonction de répartition \(F(x)\), l'A. considère la classe \(K\) de toutes les fonctions de répartition de la forme \(F(ax+b)\). Il cherche à définir la distance de deux classes. Pour cela il introduit la convolution \[ \tilde F(x) = \int_{-\infty}^\infty F(x-y) \,d[1 - F(-y)]\text{ de }F(x)\text{ et de }1-F(-x), \] la fonction de ...
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Convergence Estimates for the Distribution of Trailing Digits
Journal of the ACM, 1976This paper analyzes the distribution of trailing digits (tail end digits) of positive real floating-point numbers represented in arbitrary base β and randomly chosen from a logarithmic distribution. The analysis shows that the n th digit for n ≥ 2 is actually ...
Alan Feldstein, Richard Goodman
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Topology in a Group and Convergence of Distributions
Theory of Probability & Its Applications, 1964The purpose of this paper is to prove the following result. Let $\xi _1 ,\xi _2 , \cdots ,\xi _n , \cdots $ be an arbitrary sequence of independent random variables on a locally compact group G. We construct the compositions \[ \xi _n = \xi _1 \xi _2 \cdots \xi _n . \] If elements $a_n \in G$ can be found so that the sequence of normalized compositions
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Convergence in Distribution for Best-Fit Decreasing
SIAM Journal on Computing, 1996Let \(X_1,X_2,\dots,X_n\) be independent random variables, uniformly distributed over \([0,1]\), that represent items sizes and let \(B_n\) be the number of bins needed to pack items of these sizes using the best-fit decreasing algorithm. The authors prove that the sequence of random variables \(n^{-1/2}(B_n-{n\over 2})\), \(n\geq 1\), converges in ...
Wansoo T. Rhee, Michel Talagrand
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Note on the Convergence of a Manpower Distribution
Journal of the Operational Research Society, 1992Summary: An estimate of the rate of convergence to its limit is given of the stochastic matrix describing the structure at time \(t\) of a stratified population in which the proportional wastage is compensated by recruitment to the lowest rank. An example is given.
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1991
We examine some aspects of the theory of distributions, not in the usual locally convex topological vector space \((lcs)\) setting but in the more general convergence vector space \((cvs)\) framework. The spaces \({\mathcal D},{\mathcal E}'\), and \({\mathcal D}'\) of test functions and distributions are equipped with their canonical \(cvs\) structures
Beattie, Ronald, Butzmann, Heinz-Peter
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We examine some aspects of the theory of distributions, not in the usual locally convex topological vector space \((lcs)\) setting but in the more general convergence vector space \((cvs)\) framework. The spaces \({\mathcal D},{\mathcal E}'\), and \({\mathcal D}'\) of test functions and distributions are equipped with their canonical \(cvs\) structures
Beattie, Ronald, Butzmann, Heinz-Peter
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Convergence in a sparse distributed memory
Proceedings 5th Brazilian Symposium on Neural Networks (Cat. No.98EX209), 2002A method for converging in the sparse distribution memory, utilizing the Jaeckel activation mechanism, is presented. This is done by identifying the possible errors in the address.
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Convergence in distribution and Skorokhod Convergence for the general theory of processes
Probability Theory and Related Fields, 1991This paper proves some Skorokhod convergence theorems for processes with filtration. Roughly, these are theorems which say that if a family of processes with filtration \((X^ n,{\mathcal F}^ n)\), \(n\in {\mathbb{N}}\), converges in distribution in a suitable sense, then there exists a family of equivalent processes \((Y^ n,{\mathcal G}^ n)\), \(n\in {\
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