Robust Prediction Operations for Stationary Processes.

Abstract

This paper considers prediction for stationary processes, in environments where data outliers may be present. The develops a sequence of outlier resistant prediction operations, which is 'uniformly qualitatively robust. Studied are the asymptotic mean-squared performance of the developed operations, both in the absence and the presence of i.i.d. data outliers. Important performance characteristics studied include the breakdown point and the influence function. (Author)

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Document Details

Document Type
Technical Report
Publication Date
Aug 18, 1987
Accession Number
ADA185408

Entities

People

  • P. P. Kazakos

Organizations

  • University of Virginia

Tags

Communities of Interest

  • Biomedical
  • Space

DTIC Thesaurus Topics

  • Air Force
  • Air Force Facilities
  • Applied Mathematics
  • Business Administration
  • Calculus Of Variations
  • Contracts
  • Electrical Engineering
  • Engineering
  • Gaussian Processes
  • Materials
  • Materials Science
  • Probability
  • Random Variables
  • Scientific Research
  • Stationary Processes
  • Statistics
  • Stochastic Processes

Fields of Study

  • Mathematics

Readers

  • Statistical inference.