On Gibbs sampling for state space models
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Summary
This work shows how to use the Gibbs sampler to carry out Bayesian inference on a linear state space model with errors that are a mixture of normals and coefficients that can switch over time.
- Type
- article
- Published
- 1994-09-01
- Cited by
- 2,279
- References
- 17
- OpenAlex
- https://openalex.org/W2121448470
- Semantic Scholar
- https://api.semanticscholar.org/CorpusID:122959783
Keywords
Mathematics, Gibbs sampling, State space, Sampling (signal processing), State (computer science)
References
- Bayesian "Confidence Intervals" for the Cross-validated Smoothing Spline
- A Monte Carlo Approach to Nonnormal and Nonlinear State-Space Modeling
- Evaluation of likelihood functions for Gaussian signals
- A bayesian approach to some outlier problems.
- A new algorithm for spline smoothing based on smoothing a stochastic process
- Modeling and Monitoring Biomedical Time Series
- Estimation, Filtering, and Smoothing in State Space Models with Incompletely Specified Initial Conditions
- The estimation of standard errors in Monte Carlo simulation experiments
- A Smoothness Priors–State Space Modeling of Time Series with Trend and Seasonality
- A New Approach to the Economic Analysis of Nonstationary Time Series and the Business Cycle
- Sampling-Based Approaches to Calculating Marginal Densities
- FILTERING AND SMOOTHING IN STATE SPACE MODELS WITH PARTIALLY DIFFUSE INITIAL CONDITIONS
- Dynamic linear models with switching
- Robustification of Kalman Filter Models
- Markov Chains for Exploring Posterior Distributions
- Covariance structure of the Gibbs sampler with applications to the comparisons of estimators and augmentation schemes
- Optimal Filtering
Cited by
- Stochastic volatility model with regime-switching skewness in heavy-tailed errors for exchange rate returns
- Essays in cross-sectional asset pricing
- Essays in structural macroeconometrics
- Historical Developments in Bayesian Econometrics after Cowles Foundation Monographs 10, 14
- Bayesian detection of abnormal segments in multiple time series
- Bayesian Estimation of State-Space Model Using the Hybrid Monte Carlo within Gibbs Sampler
- A multivariate threshold stochastic volatility model
- Model Selection for a Class of Spatio-temporal Models for Areal Data
- Bayesian Learning about Ideal Points of U.S. Supreme Court Justices, 1953-1999∗
- Bayesian inference for time series with heavy-tailed symmetric α-stable noise processes
- Liquidity, inflation and asset prices in a timevarying framework for the euro area. NBB Working Papers. No. 142, 16 October 2008
- State Space Modelling of Dynamic Choice Behavior with Habit Persistence
- How Euro-Area Sovereign Spreads Respond to Shocks? A TVP-FAVAR Model
- Particle learning for Bayesian non-parametric Markov Switching Stochastic Volatility model
- GIBBS SAMPLING ON A STEADY MODEL
- SPDE based modeling of large space-time data sets
- Time Instability of the U.S. Monetary System: Multiple Break Tests and Reduced Rank TVP VAR
- Robust Recursive Kalman-Filtering
- Essays on Risk Measurement and Modeling in Macroeconomics and Finance
- Nonlinearities, smoothing and countercyclical monetary policy
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