An Introduction to Functional Central Limit Theorems for Dependent Stochastic Processes

This paper shows how the modern machinery for generating abstract empirical central limit theorems can be applied to arrays of dependent variables. It develops a bracketing approximation (closely related to results of Philipp and Massart) based on a moment inequality for sums of strong mixing arrays...

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Veröffentlicht in:	International statistical review 1994-04, Vol.62 (1), p.119-132
Hauptverfasser:	Donald W. K. Andrews, Pollard, David
Format:	Artikel
Sprache:	eng
Schlagworte:	Approximation Banach space Central limit theorem Coefficients Exact sciences and technology Integers Limit theorems Mathematical moments Mathematical theorems Mathematics Perceptron convergence procedure Probability and statistics Probability theory and stochastic processes Random variables Sciences and techniques of general use Stochastic processes
Online-Zugang:	Volltext
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