AIC, overfitting principles, and the boundedness of moments of inverse matrices for vector autotregressions and related models.
type: Item
instance of: scholarly article
title: AIC, overfitting principles, and the boundedness of moments of inverse matrices for vector autotregressions and related models.
zbMATH Open document ID: 1180.62120
author: David F. Findley
author: Ching-Zong Wei
published in: Journal of Multivariate Analysis
publication date: 2003-03-16T00:00:00Z
Mathematics Subject Classification ID: 62M10
Mathematics Subject Classification ID: 62H10
Mathematics Subject Classification ID: 62H99
zbMATH DE Number: 1882308
zbMATH Keywords: model selection
zbMATH Keywords: misspecified models
zbMATH Keywords: principle of parsimony
zbMATH Keywords: least squares matrices
zbMATH Keywords: uniform
zbMATH Keywords: Lipschitz condition
zbMATH Keywords: elliptical distributions
MaRDI profile type: Publication
full work available at URL: jmva.2001.2063
OpenAlex ID: W2072993649
cites work: Q4769776
cites work: Q4040352
cites work: A derivation of the information criteria for selecting autoregressive models
cites work: Convergence of moments of least squares estimators for the coefficients of an autoregressive process of unknown order
cites work: Asymptotic properties of spectral estimates of second order
cites work: ON THE UNBIASEDNESS PROPERTY OF AIC FOR EXACT OR APPROXIMATING LINEAR STOCHASTIC TIME SERIES MODELS
cites work: Counterexamples to parsimony and BIC
cites work: Q4246619
cites work: A conversation with Hirotugu Akaike
cites work: Q4840383
cites work: Subsampling and model selection in time series analysis
cites work: Corrigenda: Properties of Predictors for Autoregressive Time Series
cites work: The asymptotic distribution of serial covariances
cites work: A central limit theorem for stationary processes and the parameter estimation of linear processes
cites work: Breakthroughs in statistics. Volume I: Foundations and basic theory
cites work: On Information and Sufficiency
cites work: PREDICTION ERROR OF MULTIVARIATE TIME SERIES WITH MIS-SPECIFIED MODELS
cites work: Convergence analysis of parametric identification methods
cites work: Q3219581
cites work: Statistical identification for optimal control of supercritical thermal power plants
cites work: Maximum likelihood estimates of incorrect Markov models for time series and the derivation of AIC
cites work: A new ship's auto pilot design through a stochastic model
cites work: On a distributional bound arising in autoregressive model fitting
cites work: Selected papers of Hirotugu Akaike
cites work: Q3323077
cites work: Q3996430
cites work: Q3747471
cites work: Asymptotically efficient selection of the order of the model for estimating parameters of a linear process
cites work: Entropy maximization principle and selection of the order of an autoregressive Gaussian process
cites work: Sequential shrinkage estimation in the general linear model
cites work: Discussion, Emphasizing the Connection between Analysis of Variance and Spectrum Analysis
cites work: Likelihood Ratio Tests for Model Selection and Non-Nested Hypotheses
cites work: Asymptotic Inference about Predictive Ability
DOI: 10.1006/JMVA.2001.2063
description: scientific article; zbMATH DE number 1882308