Robust Prediction for Stationary Processes. 2D Enriched Version.

Abstract

Consider prediction for stationary processes, in environments where data outliers may be present. Two sequences are developed for outliers resistant prediction operations, which are uniformly qualitatively robust. The asymptotic mean-squared performance of the developed operations are studied in the absence of data outliers. Important performance characteristics studied include the breakdown point and the influence function. Included are numerical results, for some autoregressive nominal processes.

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Document Details

Document Type
Technical Report
Publication Date
Nov 24, 1987
Accession Number
ADA193318

Entities

People

  • Kailash Birmiwal
  • P. Papantoni-kazakos

Organizations

  • University of Virginia

Tags

Communities of Interest

  • Biomedical

DTIC Thesaurus Topics

  • Air Force
  • Air Force Facilities
  • Applied Mathematics
  • Business Administration
  • Electrical Engineering
  • Engineering
  • Gaussian Processes
  • Materials Science
  • Mathematics
  • Random Variables
  • Sequences
  • Stationary
  • Stationary Processes
  • Statistics
  • Stochastic Processes
  • Systems Engineering
  • Two Dimensional

Fields of Study

  • Mathematics

Readers

  • Statistical inference.
  • Systems Analysis and Design