ON THE PROBABILITY OF ERROR WHEN USING A GENERAL AKAIKE-TYPE CRITERION TO ESTIMATE AUTOREGRESSION ORDER

DOI10.1111/j.1467-9892.1993.tb00150.xzbMath0780.62066OpenAlexW2039198986MaRDI QIDQ3141187

Hall, Peter, Jeffrey D. Hart

Publication date: 2 February 1994

Published in: Journal of Time Series Analysis (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1111/j.1467-9892.1993.tb00150.x

zbMATH Keywords

weak consistencyoverestimationinformation criteriaAR(1) processtime series modellingadditive penaltyconstant of proportionalityautoregression ordergeneral Akaike-type procedureprobability of underestimating orderproperties of error probabilities

Mathematics Subject Classification ID

Time series, auto-correlation, regression, etc. in statistics (GARCH) (62M10) Large deviations (60F10)

Cites Work

• Modeling by shortest data description
• An objective use of Bayesian models
• The estimation of the order of an ARMA process
• Estimating the dimension of a model
• Fitting autoregressive models for prediction
• Non-Uniform Estimates, Moderate and Large Deviations in the Central Limit Theorem form-Dependent Random Variables
• On the Relationship Between the S Array and the Box-Jenkins Method of ARMA Model Identification
• A method for the derivation of limit theorems for sums of m-dependent random variables

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