A functional central limit theorem for transformed solutions of the multidimensional Burgers equation with random initial data

Research output: Contribution to journalArticle

Abstract

This paper states the convergence in distribution in some functional space to the Gaussian field with explicitly calculated parameters for transformed solutions of the multidimensional Burgers equation with initial conditions given by the associated random measure. Auxiliary moment and maximal inequalities obtained in the paper are of interest in themselves.

Original languageEnglish (US)
Pages (from-to)387-405
Number of pages19
JournalTheory of Probability and its Applications
Volume46
Issue number3
DOIs
StatePublished - 2002

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Moment Inequalities
Convergence in Distribution
Maximal Inequality
Functional Central Limit Theorem
Gaussian Fields
Random Measure
Burgers Equation
Initial conditions
Central limit theorem

Keywords

  • Associated random variables
  • Maximal inequalities
  • Moment inequalities
  • Nonlinear diffusion

ASJC Scopus subject areas

  • Statistics and Probability

Cite this

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title = "A functional central limit theorem for transformed solutions of the multidimensional Burgers equation with random initial data",
abstract = "This paper states the convergence in distribution in some functional space to the Gaussian field with explicitly calculated parameters for transformed solutions of the multidimensional Burgers equation with initial conditions given by the associated random measure. Auxiliary moment and maximal inequalities obtained in the paper are of interest in themselves.",
keywords = "Associated random variables, Maximal inequalities, Moment inequalities, Nonlinear diffusion",
author = "Yuri Bakhtin",
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journal = "Theory of Probability and its Applications",
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