Title: Prediction focussed model selection for autoregressive models
Authors: Claeskens, Gerda ×
Croux, Christophe
Van Kerckhoven, Johan #
Issue Date: 2007
Publisher: Blackwell Publishers
Series Title: Australian & New Zealand journal of statistics vol:49 pages:359-379
Abstract: In order to make predictions of future values of a time
series, one needs to specify a forecasting model. A popular choice is an autoregressive time series model, where the order of the model is chosen by an information criterion. We propose an extension of the Focussed Information Criterion (FIC) for model-order selection with focus on a high predictive accuracy (i.e. the mean squared forecast error is low). We obtain theoretical results and illustrate via a simulation study and some real data examples that the FIC is a valid alternative to AIC and BIC for selection of a prediction model. We also illustrate the possibility of using FIC for purposes other than forecasting, and explore its use in an extended model.
ISSN: 1369-1473
Publication status: published
KU Leuven publication type: IT
Appears in Collections:Research Center for Operations Research and Business Statistics (ORSTAT), Leuven
× corresponding author
# (joint) last author

Files in This Item:

There are no files associated with this item.

Request a copy


All items in Lirias are protected by copyright, with all rights reserved.

© Web of science