Sequential Bayesian inference for vector autoregressions with stochastic volatility
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Publication:2181522
DOI10.1016/j.jedc.2020.103851OpenAlexW2994868957MaRDI QIDQ2181522
Publication date: 19 May 2020
Published in: Journal of Economic Dynamics \& Control (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1016/j.jedc.2020.103851
stochastic volatilitysequential Monte Carlovector autoregressionsparticle filterRao-Blackwellization
Related Items (2)
Comparing stochastic volatility specifications for large Bayesian VARs ⋮ Comment on ``Large Bayesian vector autoregressions with stochastic volatility and non-conjugate priors
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Cites Work
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- On particle methods for parameter estimation in state-space models
- Methods for inference in large multiple-equation Markov-switching models
- On adaptive resampling strategies for sequential Monte Carlo methods
- Stochastic volatility with leverage: fast and efficient likelihood inference
- A comparison of programming languages in macroeconomics
- Central limit theorem for sequential Monte Carlo methods and its application to Bayesian inference
- Following a Moving Target—Monte Carlo Inference for Dynamic Bayesian Models
- Sequential Monte Carlo Methods in Practice
- Julia: A Fresh Approach to Numerical Computing
- Real-Time Density Forecasts From Bayesian Vector Autoregressions With Stochastic Volatility
- Sequential Monte Carlo Samplers
- Dynamic Conditional Independence Models and Markov Chain Monte Carlo Methods
- Time Varying Structural Vector Autoregressions and Monetary Policy: A Corrigendum
- A Survey of Sequential Monte Carlo Methods for Economics and Finance
- Adaptive Sequential Posterior Simulators for Massively Parallel Computing Environments
- Bayesian Inference for ARFIMA Models
- The Bayesian Choice
- Time Varying Structural Vector Autoregressions and Monetary Policy
- SMC2: An Efficient Algorithm for Sequential Analysis of State Space Models
- Getting It Right
- Estimation and Forecasting in Models with Multiple Breaks
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