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  • 标题:Information and Prediction Criteria in Selecting the Forecasting Model
  • 本地全文:下载
  • 作者:Mariola Piłatowska ; Mariola Piłatowska
  • 期刊名称:Dynamic Econometric Models
  • 印刷版ISSN:1234-3862
  • 电子版ISSN:2450-7067
  • 出版年度:2011
  • 卷号:11
  • 页码:21-40
  • DOI:10.12775/DEM.2011.002
  • 语种:English
  • 出版社:Nicolaus Copernicus University Press
  • 摘要:The purpose of the paper it to compare the performance of both information and prediction criteria in selecting the forecasting model on empirical data for Poland when the data generating model is unknown. The attention will especially focus on the evolution of information criteria (AIC, BIC) and accumulated prediction error (APE) for increasing sample sizes and rolling windows of different size, and also the impact of initial sample and rolling window sizes on the selection of forecasting model. The best forecasting model will be chosen from the set including three models: autoregressive model, AR (with or without a deterministic trend), ARIMA model and random walk (RW) model.
  • 关键词:information and prediction criteria; accumulated prediction error; model selection
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