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AUTO-REGRESSIVE INTEGRATED MOVING AVERAGE PROCESS [1 record]

Record 1 2000-06-27

English

Subject field(s)
  • Statistical Methods
DEF

A modeling process by which variation in a time series are assumed to be explained wholly by the historical trends of the data itself. In essence, the ARIMA modeling process consists of the autoregressive and moving average processes of the Auto-Regressive Moving Average (ARMA) Model process on data that have been Differenced to render them Stationary. The process uses variations of differencing and transformations to describe historical patterns in the data. Like the simpler ARMA model, forecasts made by an ARIMA modeling process consist of only a mathematical process of projecting inherent characteristics of trend, cycles, and seasonality into the future and incorporate no economic relatinships. Consequently, such models are not appropriate for impact analysis or for incorporating random "shocks", but may prove an effective estimation process when the trends in the historical data are relatively stable and well-behaved.

OBS

The X-11 ARIMA process is used to detect and remove the seasonality from the original data.

French

Domaine(s)
  • Méthodes statistiques
OBS

Dans divers travaux d'économétrie on fait [...] usage de processus mixtes, dits «autorégressifs de moyennes mobiles» [...].

Spanish

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