A Study on Lebesgue Decomposition of Measures Induced by Stable Processes.

Abstract

The Lebesgue decomposition of measures induced by symmetric stable process is considered. An upper bound for the set of admissible translates of a general pth order process is presented, which is a partial analog of the reproducing kernel Hilbert space of a second order process. For invertible processes a dichotomy is established: each translate is either admissible or singular, and the admissible translates are characterized. As a consequence, most continuous time moving averages and all harmonizable processes with nonatomic spectral measure have no admissible translate. Necessary and sufficient conditions for equivalence and singularity of certain product measures are given and applied to the problem of distinguishing a sequence of random vectors from affine transformations of itself; in particular sequences of stable random variables are considered and the singularity of sequences with different indexes of stability is proved. Sufficient conditions for singularity and necessary conditions for absolute continuity are given for the pth order processes. Finally the dichotomy 'two processes are either equivalent or singular', is shown to hold for certain stable processes such as independently scattered random measures and harmonizable processes.

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Document Details

Document Type
Technical Report
Publication Date
Nov 01, 1987
Accession Number
ADA192893

Entities

People

  • Mauro S. De Freitas Marques

Organizations

  • University of North Carolina at Chapel Hill

Tags

DTIC Thesaurus Topics

  • Banach Space
  • Data Science
  • Detection
  • Differential Equations
  • Equations
  • Gaussian Processes
  • Hilbert Space
  • Information Science
  • Mathematics
  • North Carolina
  • Probability
  • Random Variables
  • Sequences
  • Statistical Algorithms
  • Statistics
  • Stochastic Processes
  • Surveys

Fields of Study

  • Mathematics

Readers

  • Calculus or Mathematical Analysis
  • Mathematical Modeling and Probability Theory.

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  • Space