A Graphical Similarity Measure for Time Series Models.

Abstract

The purpose of this document is to introduce a graphical device useful as a measure of similarity or as a goodness of fit criterion for hypothesized time series models. It is based on the actual oscillation observed in time series as depicted by axis-crossings and higher order crossings. Higher order crossings (HOC) are axis-crossings of differenced time series and are closely linked to the spectral content of the series. In fact under the Gaussian assumption, to which we shall adhere, HOC determine the finite dimensional distributions up to a scale parameter given that the mean is zero. The main advantage of HOC is that they are easily obtained from an observed series and that only very few of them are needed, as the dicriminatory power in HOC usually diminishes with their order. Higher order crossings in time series discrimination were discussed in Kedem and Slud (1981), (1982), where a certain goodness of fit criterion is suggested, Here however the emphasis is on a graphical device rather than a single test statistic. This graphical method may be shown useful in answering the question 'Does a given time series oscillate as a certain hypothesized model?' Some examples with real and simulated data demonstrate the use and potential of this method.

Open PDF

Document Details

Document Type
Technical Report
Publication Date
Apr 01, 1985
Accession Number
ADA158869

Entities

People

  • B. Kedem

Organizations

  • University of Maryland

Tags

Communities of Interest

  • Energy and Power Technologies

DTIC Thesaurus Topics

  • Abstracts
  • Algorithms
  • Asymptotic Normality
  • Classification
  • Computer Programs
  • Crossings
  • Data Science
  • Discrimination
  • Distribution Functions
  • Gaussian Processes
  • Information Science
  • Maryland
  • Mathematics
  • Oscillation
  • Probability
  • Universities
  • White Noise

Readers

  • Approximation Theory.
  • Regression Analysis.
  • Systems Analysis and Design