Forecasting ARMA models: a comparative study of information criteria focusing on MDIC
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Publication:5306304
DOI10.1080/00949650802464137zbMath1185.62166OpenAlexW2164316620MaRDI QIDQ5306304
Panagiotis Mantalos, Alex Karagrigoriou, Kyriacos Mattheou
Publication date: 8 April 2010
Published in: Journal of Statistical Computation and Simulation (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1080/00949650802464137
tablesmodel selectionARMA processinformation criterionmodified divergence information criterion (MDIC)NMSFE
Inference from stochastic processes and prediction (62M20) Time series, auto-correlation, regression, etc. in statistics (GARCH) (62M10)
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Statistical inference for multinomial populations based on a double index family of test statistics ⋮ Bootstrapping the augmented Dickey–Fuller test for unit root using the MDIC ⋮ On properties of the \((\Phi , a)\)-power divergence family with applications in goodness of fit tests ⋮ A discrete probabilistic model for analyzing pairwise comparison matrices
Cites Work
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- An improved Akaike information criterion for state-space model selection
- Bootstrap variants of the Akaike information criterion for mixed model selection
- Asymptotically efficient selection of the order by the criterion autoregressive transfer function
- Asymptotically efficient selection of the order of the model for estimating parameters of a linear process
- The estimation of the order of an ARMA process
- Estimating the dimension of a model
- Bootstrapping log likelihood and EIC, an extension of AIC
- On the quantile process based on the autoregressive residuals.
- Fitting autoregressive models for prediction
- Bootstrap Choice of Estimators in Parametric and Semiparametric Families: An Extension of EIC
- Regression and time series model selection in small samples
- An optimal selection of regression variables
- Robust and efficient estimation by minimising a density power divergence
- Assessing the predictive influence of cases in a state space process
- A Method for Analyzing Supersaturated Designs with a Block Orthogonal Structure
- On Information and Sufficiency
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