Automatic Modeling Methods for Univariate Series
AbstractIn this article, a unified approach to automatic modeling for univariate series is presented. First, ARIMA models and the classical methods for fitting these models to a given time series are reviewed. Second, some objective methods for model identification are considered and some algorithmical procedures for automatic model identification are described. Third, outliers are incorporated into the model and an algorithm, for automatic model identification in the presence of outliers is proposed.
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Bibliographic InfoPaper provided by Banco de Espa�a in its series Banco de Espa�a Working Papers with number 9808.
Length: 50 pages
Date of creation: 1998
Date of revision:
MODELS ; TIME SERIES;
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- C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models
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