Modelling extremes of time-dependent data by Markov-switching structures
From MaRDI portal
Publication:1011533
DOI10.1016/j.jspi.2008.08.022zbMath1159.62056OpenAlexW2039409870MaRDI QIDQ1011533
Publication date: 8 April 2009
Published in: Journal of Statistical Planning and Inference (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1016/j.jspi.2008.08.022
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) Markov processes: estimation; hidden Markov models (62M05)
Uses Software
Cites Work
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Tail behaviour and extremes of two-state Markov-switching autoregressive models
- A two-state regime switching autoregressive model with an application to river flow analysis
- Subsampling techniques and the jackknife methodology in the estimation of the extremal index
- Extremal behaviour of stationary Markov chains with applications
- Autoregressive conditional heteroskedasticity and changes in regime
- A sufficiency property arising from the characterization of extremes of Markov chains
- The extremal index for a Markov chain
- Limit laws for the maxima of chain-dependent sequences with positive extremal index
- Ergodicity of Autoregressive Processes with Markov-Switching and Consistency of the Maximum-Likelihood Estimator
- Models for the extremes of Markov chains
- Markov chain models for threshold exceedances
- The distributions of cluster functionals of extreme events in a dth-order Markov chain
- Inference for Clusters of Extreme Values
- Asymptotic location and recurrence properties of maxima of a sequence of random variables defined on a Markov chain
- An introduction to statistical modeling of extreme values
This page was built for publication: Modelling extremes of time-dependent data by Markov-switching structures
