Limit Theory for Random Coefficient First-Order Autoregressive Process

DOI10.1080/03610920902940175zbMath1318.62282OpenAlexW2033423563MaRDI QIDQ3585291

Yong Zhang, Xiao-Yun Yang

Publication date: 19 August 2010

Published in: Communications in Statistics - Theory and Methods (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/03610920902940175

zbMATH Keywords

asymptotic normalitylimit theoryconditional least squaresrandom coefficient AR(1)

Mathematics Subject Classification ID

Time series, auto-correlation, regression, etc. in statistics (GARCH) (62M10) Central limit and other weak theorems (60F05)

Related Items (5)

On the first passage time of the parabolic boundary by the Markov random walk ⋮ Empirical likelihood-based inference in generalized random coefficient autoregressive model with conditional moment restrictions ⋮ Limit theory for random coefficient autoregressive process under possibly infinite variance error sequence ⋮ Asymptotics for the conditional self-weighted M-estimator of GRCA(1) models with possibly heavy-tailed errors ⋮ Asymptotics for the random coefficient first-order autoregressive model with possibly heavy-tailed innovations

Cites Work

• Limit theory for moderate deviations from a unit root
• Random coefficient autoregressive models: an introduction
• Stopping times and tightness
• Parameter estimation for generalized random coefficient autoregressive processes
• Large sample inference for conditional exponential families with applications to nonlinear time series
• Asymptotic optimal inference for a class of nonlinear time series models
• RANDOM COEFFICIENT AUTOREGRESSIVE PROCESSES:A MARKOV CHAIN ANALYSIS OF STATIONARITY AND FINITENESS OF MOMENTS
• EMPIRICAL BAYES ESTIMATION FOR FIRST-ORDER AUTOREGRESSIVE PROCESSES
• Convergence of stochastic processes

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