Model averaging multistep prediction in an infinite order autoregressive process
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Publication:2109293
DOI10.1007/s11424-022-0311-9OpenAlexW4289516908MaRDI QIDQ2109293
Tao Jiang, Huifang Yuan, Peng Lin, Jinfeng Xu
Publication date: 20 December 2022
Published in: Journal of Systems Science and Complexity (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1007/s11424-022-0311-9
Cites Work
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- Least-squares forecast averaging
- Least squares model averaging by Mallows criterion
- Jackknife model averaging
- Asymptotically efficient selection of the order of the model for estimating parameters of a linear process
- Estimation for autoregressive moving average models in the time and frequency domains
- On same-realization prediction in an infinite-order autoregressive process.
- AIC, overfitting principles, and the boundedness of moments of inverse matrices for vector autotregressions and related models.
- Model averaging prediction for time series models with a diverging number of parameters
- Optimal crossover designs for generalized linear models
- Asymptotic optimality of the nonnegative garrote estimator under heteroscedastic errors
- Order selection for same-realization predictions in autoregressive processes
- Frequentist model averaging for threshold models
- Fitting autoregressive models for prediction
- Some recent advances in time series modeling
- Model Selection: An Integral Part of Inference
- Model Selection and Multimodel Inference
- MULTISTEP PREDICTION IN AUTOREGRESSIVE PROCESSES
- Least Squares Model Averaging
- The estimation of mixed moving average autoregressive systems
- Model averaging in a multiplicative heteroscedastic model
- Model averaging based on leave-subject-out cross-validation
- A new look at the statistical model identification
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