Asymptotics of a class of \(p\)th-order nonlinear autoregressive processes
From MaRDI portal
Publication:1305274
DOI10.1016/S0167-7152(98)00099-6zbMath0979.60021OpenAlexW2011188167MaRDI QIDQ1305274
Publication date: 17 February 2002
Published in: Statistics \& Probability Letters (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1016/s0167-7152(98)00099-6
functional central limit theoremMarkov processirreducibilityinvariant probabilitygeometrically Harris ergodic
Stationary stochastic processes (60G10) Discrete-time Markov processes on general state spaces (60J05)
Related Items
Stability of nonlinear AR-GARCH models, Strict stationarity of ar(p) processes generated by nonlinear random functions with additive perturbations, Threshold \(\text{Arch}(1)\) processes: Asymptotic inference, Towards a Unified Approach for Proving Geometric Ergodicity and Mixing Properties of Nonlinear Autoregressive Processes
Cites Work
- Markov chains and stochastic stability
- Sufficient conditions for ergodicity and recurrence of Markov chains on a general state space
- On geometric ergodicity of nonlinear autoregressive models
- Non-linear time series and Markov chains
- RANDOM COEFFICIENT AUTOREGRESSIVE PROCESSES:A MARKOV CHAIN ANALYSIS OF STATIONARITY AND FINITENESS OF MOMENTS
- On the use of the deterministic Lyapunov function for the ergodicity of stochastic difference equations
- Non-linear time series models for non-linear random vibrations
- On the functional central limit theorem and the law of the iterated logarithm for Markov processes
- AN EXAMPLE IN THE THEORY OF THE SPECTRUM OF A FUNCTION
- Unnamed Item
- Unnamed Item
- Unnamed Item
