AIC (an information criterion, or Akaike's information criterion) is a statistic definied for parametric models whose parameters have been obtained by maximizing a form a likelihood function. AIC values are compared in selecting from among competing models for a data set used for parameter estimation. The selection is prescribed by Akaike's minimum AIC criterion, hereafter MinAIC, which says that the model with smallest AIC is to be preferred.

Others in Series

Working Paper

Applied Time Series Analysis of Economic Data

1983

Work leading to currently used methods of seasonal adjustment began with the link-relative method of Persons (1919).

Working Paper

Ambiguities Associated with the Fitting of ARMA Models to Time Series

1984

Examples are presented illustrating some ambiguities associated with the application of ARMA models.

Working Paper

The Effect of Sampling Error on the Time Series Behavior

1993

Much empirical economic research today involves estimation of tightly specified time series models that derive from theoretical optimization problems.

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Related Information

Time Series and Seasonal Adjustment Working Papers

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