On asymptotic risk of selecting models for possibly nonstationary time-series
From MaRDI portal
Publication:5861039
DOI10.1080/07474938.2020.1777709zbMath1490.62284OpenAlexW3035910598MaRDI QIDQ5861039
Publication date: 4 March 2022
Published in: Econometric Reviews (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1080/07474938.2020.1777709
asymptotic risksame-realization predictionAIC-type information criteriaBIC-type information criteriahigh-dimensional analysesstrongly sparse
Applications of statistics to economics (62P20) Inference from stochastic processes and prediction (62M20) Time series, auto-correlation, regression, etc. in statistics (GARCH) (62M10)
Cites Work
- Unnamed Item
- Unnamed Item
- The Adaptive Lasso and Its Oracle Properties
- On the selection of forecasting models
- Least-squares forecast averaging
- Cointegrating rank selection in models with time-varying variance
- Least squares model averaging by Mallows criterion
- On model selection from a finite family of possibly misspecified time series models
- Jackknife model averaging
- Order selection in nonstationary autoregressive models
- Model selection for integrated autoregressive processes of infinite order
- Conditional predictive inference post model selection
- Toward optimal model averaging in regression models with time series errors
- Adaptive prediction by least squares predictors in stochastic regression models with applications to time series
- Asymptotic optimality for \(C_ p\), \(C_ L\), cross-validation and generalized cross-validation: Discrete index set
- Limiting distributions of least squares estimates of unstable autoregressive processes
- The estimation of the order of an ARMA process
- Estimation of the mean of a multivariate normal distribution
- On the dominance of Mallows model averaging estimator over ordinary least squares estimator
- Regular variation of GARCH processes.
- On same-realization prediction in an infinite-order autoregressive process.
- Evaluating panel data forecasts under independent realization
- Model selection for high-dimensional linear regression with dependent observations
- Order selection for possibly infinite-order non-stationary time series
- Order selection for same-realization predictions in autoregressive processes
- Model averaging by jackknife criterion in models with dependent data
- On the ``degrees of freedom of the lasso
- On functional limits of short- and long-memory linear processes with GARCH(1,1) noises
- Accumulated prediction errors, information criteria and optimal forecasting for autoregressive time series
- CONSISTENT AND CONSERVATIVE MODEL SELECTION WITH THE ADAPTIVE LASSO IN STATIONARY AND NONSTATIONARY AUTOREGRESSIONS
- Distribution of the Estimators for Autoregressive Time Series With a Unit Root
- Inference in Linear Time Series Models with some Unit Roots
- Semiparametric cointegrating rank selection
- PREDICTION ERRORS IN NONSTATIONARY AUTOREGRESSIONS OF INFINITE ORDER
- Testing for a unit root in time series regression
- Likelihood Ratio Statistics for Autoregressive Time Series with a Unit Root
- Selection of the order of an autoregressive model by Akaike's information criterion
- Adaptive Model Selection
- Model averaging, asymptotic risk, and regressor groups
- Econometric Model Determination
- ASYMPTOTICALLY EFFICIENT MODEL SELECTION FOR PANEL DATA FORECASTING
- AUTOMATED ESTIMATION OF VECTOR ERROR CORRECTION MODELS
- Least Squares Model Averaging
- The Risk of James–Stein and Lasso Shrinkage
- Model averaging based on leave-subject-out cross-validation