Influential Observations in Time Series.

Abstract

This paper studies how to identify influential observations in univariate ARIMA time series models and how to measure their effects on the estimated parameters of the model. The sensitivity of the parameters to the presence of either additive or innovational outliers is analyzed, and influence statistics based on the Mahalanobis distance are presented. The statistic linked to additive outliers is shown to be very useful to indicate the robustness of the fitted model to the given data set. Its application is illustrated using simulation results and a relevant set of historical data. (Author)

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Document Details

Document Type
Technical Report
Publication Date
Jul 01, 1984
Accession Number
ADA144719

Entities

People

  • D. Pena

Organizations

  • University of Wisconsin–Madison

Tags

Communities of Interest

  • Materials and Manufacturing Processes

DTIC Thesaurus Topics

  • Contracts
  • Data Analysis
  • Data Science
  • Data Sets
  • Equations
  • Estimators
  • Information Science
  • Mathematics
  • Probability
  • Sensitivity
  • Simulations
  • Standards
  • Statistics
  • Stochastic Processes
  • United States
  • Universities
  • Wisconsin

Fields of Study

  • Mathematics

Readers

  • Regression Analysis.
  • Statistical inference.