Model selection under nonstationarity: Autoregressive models and stochastic linear regression models
type: Item
instance of: scholarly article
title: Model selection under nonstationarity: Autoregressive models and stochastic linear regression models
zbMATH Open document ID: 0683.62049
author: Benedikt M. Pötscher
published in: The Annals of Statistics
publication date: 1989-01-01T00:00:00Z
Mathematics Subject Classification ID: 62M10
Mathematics Subject Classification ID: 62J05
Mathematics Subject Classification ID: 60G10
Mathematics Subject Classification ID: 62F12
zbMATH DE Number: 4119444
zbMATH Keywords: model selection
zbMATH Keywords: order estimation
zbMATH Keywords: nonstationarity
zbMATH Keywords: nonergodic models
zbMATH Keywords: Akaike information criterium
zbMATH Keywords: sufficient conditions for strong consistency of estimators
zbMATH Keywords: order of general nonstationary autoregressive models
zbMATH Keywords: AIC
zbMATH Keywords: time-dependent error variance
zbMATH Keywords: regressor selection
zbMATH Keywords: stochastic regression models
MaRDI profile type: Publication
full work available at URL: https://doi.org/10.1214/aos/1176347267
OpenAlex ID: W2087104794
DOI: 10.1214/AOS/1176347267
description: scientific article; zbMATH DE number 4119444