On model selection from a finite family of possibly misspecified time series models

DOI10.1214/18-AOS1706zbMath1418.62333OpenAlexW2909437707WikidataQ128567386 ScholiaQ128567386MaRDI QIDQ666592

Ching-Kang Ing, Howell Tong, Hsiang-Ling Hsu

Publication date: 6 March 2019

Published in: The Annals of Statistics (Search for Journal in Brave)

Full work available at URL: https://projecteuclid.org/euclid.aos/1547197248

zbMATH Keywords

AICBIChigh-dimensional misspecified modelsmisspecification-resistant information criterionmultistep prediction errororthogonal greedy algorithm

Mathematics Subject Classification ID

Asymptotic properties of parametric estimators (62F12) Inference from stochastic processes and prediction (62M20) Time series, auto-correlation, regression, etc. in statistics (GARCH) (62M10) Statistical aspects of information-theoretic topics (62B10)

Related Items (12)

Negative Moment Bounds for Stochastic Regression Models with Deterministic Trends and Their Applications to Prediction Problems ⋮ A generalized information criterion for high-dimensional PCA rank selection ⋮ Strongly consistent model selection for general causal time series ⋮ An empirical study on the parsimony and descriptive power of TARMA models ⋮ Consistent model selection criteria and goodness-of-fit test for common time series models ⋮ On consistency for time series model selection ⋮ Positive-definite thresholding estimators of covariance matrices with zeros ⋮ Estimation and variable selection for high-dimensional spatial dynamic panel data models ⋮ Revisiting the Canadian Lynx Time Series Analysis Through TARMA Models ⋮ Variable selection for high-dimensional regression models with time series and heteroscedastic errors ⋮ Nonsparse Learning with Latent Variables ⋮ On asymptotic risk of selecting models for possibly nonstationary time-series

Cites Work

• Unnamed Item
• Unnamed Item
• Unnamed Item
• Regularized estimation in sparse high-dimensional time series models
• A stepwise regression method and consistent model selection for high-dimensional sparse linear models
• VAR forecasting under misspecification
• On the selection of forecasting models
• Cross-validation for selecting a model selection procedure
• Feature matching in time series modeling
• Uniform moment bounds of Fisher's information with applications to time series
• Parametric or nonparametric? A parametricness index for model selection
• Asymptotic properties of criteria for selection of variables in multiple regression
• Approximating data
• Asymptotic optimality for \(C_ p\), \(C_ L\), cross-validation and generalized cross-validation: Discrete index set
• Asymptotically efficient selection of the order of the model for estimating parameters of a linear process
• On predictive least squares principles
• Counterexamples to parsimony and BIC
• Consistent nonparametric regression. Discussion
• Estimating the dimension of a model
• 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.
• Information criteria for selecting possibly misspecified parametric models
• Akaike's information criterion and recent developments in information complexity
• Evaluating panel data forecasts under independent realization
• Order selection for same-realization predictions in autoregressive processes
• Simultaneous analysis of Lasso and Dantzig selector
• Accumulated prediction errors, information criteria and optimal forecasting for autoregressive time series
• Forward Regression for Ultra-High Dimensional Variable Screening
• A strongly consistent procedure for model selection in a regression problem
• An optimal selection of regression variables
• Selection of the order of an autoregressive model by Akaike's information criterion
• Generalised information criteria in model selection
• Model Selection and Multimodel Inference
• MULTISTEP PREDICTION IN AUTOREGRESSIVE PROCESSES
• PREDICTION/ESTIMATION WITH SIMPLE LINEAR MODELS: IS IT REALLY THAT SIMPLE?
• Sure Independence Screening for Ultrahigh Dimensional Feature Space
• Catching up Faster by Switching Sooner: A Predictive Approach to Adaptive Estimation with an Application to the AIC–BIC Dilemma
• MULTISTEP PREDICTION OF PANEL VECTOR AUTOREGRESSIVE PROCESSES
• Some Comments on C P
• Model Selection Principles in Misspecified Models
• Performance bounds for parameter estimates of high-dimensional linear models with correlated errors
• A new look at the statistical model identification

This page was built for publication: On model selection from a finite family of possibly misspecified time series models