Selection between models through multi-step-ahead forecasting

DOI10.1016/j.jspi.2010.04.032zbMath1404.62089OpenAlexW2084043346MaRDI QIDQ993804

David F. Findley, Tucker S. McElroy

Publication date: 20 September 2010

Published in: Journal of Statistical Planning and Inference (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.jspi.2010.04.032

zbMATH Keywords

model selectiontime seriesmisspecified modelsARIMA modelsincorrect modelsDiebold-Mariano testsparameter estimation effects

Mathematics Subject Classification ID

Time series, auto-correlation, regression, etc. in statistics (GARCH) (62M10) Parametric hypothesis testing (62F03) Asymptotic properties of parametric tests (62F05)

Related Items (6)

Forecasting continuous-time processes with applications to signal extraction ⋮ Comparison of non-nested models under a general measure of distance ⋮ Optimal real-time filters for linear prediction problems ⋮ Asymptotic theory of cepstral random fields ⋮ A conversation with David Findley ⋮ Multistep ahead forecasting of vector time series

Uses Software

• R
• itsmr

Cites Work

• Likelihood Ratio Tests for Model Selection and Non-Nested Hypotheses
• Signal extraction from nonstationary time series
• A local spectral approach for assessing time series model misspecification
• Time series: theory and methods.
• Counterexamples to parsimony and BIC
• Modeling of time series arrays by multistep prediction or likelihood methods.
• Asymptotic theory of statistical inference for time series
• On the integral of the squared periodogram
• Asymptotically optimal estimation in misspecified time series models
• Introduction to Time Series and Forecasting
• Model selection tests for nonlinear dynamic models
• Asymptotic Inference about Predictive Ability
• Evaluating Direct Multistep Forecasts
• Tests of equal forecast accuracy and encompassing for nested models
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