Tail behaviour and extremes of two-state Markov-switching autoregressive models

DOI10.1016/j.camwa.2007.09.008zbMath1142.62351OpenAlexW2028821110MaRDI QIDQ945187

Péter Elek, András Zempléni

Publication date: 11 September 2008

Published in: Computers \& Mathematics with Applications (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.camwa.2007.09.008

zbMATH Keywords

extremal indextail behaviourextremal clustersMarkov-switching autoregressive modelriver flow modeling

Mathematics Subject Classification ID

Time series, auto-correlation, regression, etc. in statistics (GARCH) (62M10) Applications of statistics to environmental and related topics (62P12) Statistics of extreme values; tail inference (62G32)

Related Items (2)

The distribution of the maximum of a first order autoregressive process: The continuous case ⋮ Modelling extremes of time-dependent data by Markov-switching structures

Cites Work

• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Markov chains and stochastic stability
• Analysis of time series subject to changes in regime
• A two-state regime switching autoregressive model with an application to river flow analysis
• The stochastic equation Y_n+1=A_nY_n + B_n with stationary coefficients
• Conditioned limit theorems relating a random walk to its associate, with applications to risk reserve processes and the GI/G/1 queue
• The extremal index for a Markov chain
• [https://portal.mardi4nfdi.de/wiki/Publication:4067859 Wiener-Hopf decomposition of random walks and L�vy processes]
• Markov chain models for threshold exceedances
• On stability of nonlinear AR processes with Markov switching
• Tail of the stationary solution of the stochastic equation \(Y_{n+1}=a_{n} Y_{n}+b_{n}\) with Markovian coefficients

This page was built for publication: Tail behaviour and extremes of two-state Markov-switching autoregressive models