A Review of Some Aspects of Robust Inference for Time Series.

Abstract

This paper briefly surveys some aspects of robust inference for time series, and gives an indication of the current state of knowledge in other problem areas. Basic notions of robustness are stated, and technical difficulties associated with the time series case are mentioned. Some models for time series with outliers are given. Least-squares procedures lack robustness for such models and robust alternatives are described. Issues of adaptivity versus robustness are briefly mentioned. Robustness problems involving dependency are discussed. Algorithms for robust data smoother-cleaners are briefly described, along with an application to radar glint noise. Additional keyword; Autoregression. (Author)

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Document Details

Document Type
Technical Report
Publication Date
Sep 01, 1984
Accession Number
ADA149706

Entities

People

  • R. D. Martin

Organizations

  • University of Washington

Tags

Communities of Interest

  • Energy and Power Technologies
  • Materials and Manufacturing Processes

DTIC Thesaurus Topics

  • Algorithms
  • Data Analysis
  • Data Science
  • Estimators
  • Information Processing
  • Information Science
  • Mathematics
  • Military Research
  • New York
  • Probability
  • Signal Processing
  • Statistical Algorithms
  • Statistical Analysis
  • Statistics
  • Stochastic Processes
  • Surveys
  • Universities

Readers

  • Radar Systems Engineering.
  • Statistical inference.
  • Systems Analysis and Design

Technology Areas

  • AI & ML
  • AI & ML - Machine Learning Algorithms