The law of iterated logarithm for autoregressive processes

DOI10.1155/2014/972712zbMath1407.62331OpenAlexW2153529471WikidataQ59071293 ScholiaQ59071293MaRDI QIDQ1719508

Xiaohua Hu, Mingzhi Mao, Yan Wang, Tingting He

Publication date: 8 February 2019

Published in: Mathematical Problems in Engineering (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1155/2014/972712

Mathematics Subject Classification ID

Time series, auto-correlation, regression, etc. in statistics (GARCH) (62M10) Non-Markovian processes: estimation (62M09)

Related Items

Law of the iterated logarithm for error density estimators in nonlinear autoregressive models

Cites Work

• Unnamed Item
• Unnamed Item
• Limiting mixture distributions for AR(1) model indexed by a branching process
• Markov chains and stochastic stability
• Asymptotic conditional inference for regular nonergodic models with an application to autoregressive processes
• Moderate deviation principle for autoregressive processes
• Modeling and large sample estimation for multi-casting autoregression
• The law of iterated logarithm for \(m\)-dependent Banach space valued random variables
• Some laws of the iterated logarithm in Hilbertian autoregressive models
• On Asymptotic Distributions of Estimates of Parameters of Stochastic Difference Equations
• A general law of iterated logarithm
• On the Statistical Treatment of Linear Stochastic Difference Equations