A simulation smoother for long memory time series with correlated and heteroskedastic additive noise

DOI10.1080/03610918.2018.1554120zbMath1490.62225OpenAlexW2978029140WikidataQ128519120 ScholiaQ128519120MaRDI QIDQ5083988

Mike K. P. So, Manabu Asai

Publication date: 21 June 2022

Published in: Communications in Statistics - Simulation and Computation (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/03610918.2018.1554120

zbMATH Keywords

stochastic volatilityKalman filterfilteringlong memorystate space modelssimulation smoother

Mathematics Subject Classification ID

Inference from stochastic processes and prediction (62M20) Time series, auto-correlation, regression, etc. in statistics (GARCH) (62M10)

Related Items (1)

Realized matrix-exponential stochastic volatility with asymmetry, long memory and higher-moment spillovers

Cites Work

• Adaptive proposal distribution for random walk Metropolis algorithm
• Stochastic volatility with leverage: fast and efficient likelihood inference
• On Metropolis-Hastings algorithms with delayed rejection
• Realized stochastic volatility with leverage and long memory
• Delayed rejection in reversible jump Metropolis-Hastings
• Stochastic Volatility: Likelihood Inference and Comparison with ARCH Models
• Miscellanea. Time series with additive noise
• DATA AUGMENTATION AND DYNAMIC LINEAR MODELS
• On Gibbs sampling for state space models
• A simple and efficient simulation smoother for state space time series analysis
• The simulation smoother for time series models
• An adaptive Metropolis algorithm

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