Comparison of sampling schemes for dynamic linear models
From MaRDI portal
Publication:6574125
DOI10.1111/j.1751-5823.2006.tb00170.xMaRDI QIDQ6574125
Edna A. Reis, Dani Gamerman, Esther Salazar
Publication date: 18 July 2024
Published in: International Statistical Review (Search for Journal in Brave)
Parametric inference (62Fxx) Inference from stochastic processes (62Mxx) Probabilistic methods, stochastic differential equations (65Cxx)
Cites Work
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Fast sampling of Gaussian Markov random fields
- Bayesian forecasting and dynamic models.
- Hyperparameter estimation in forecast models.
- Stochastic processes and filtering theory
- Markov chain Monte Carlo for dynamic generalised linear models
- Conditional Prior Proposals in Dynamic Models
- DATA AUGMENTATION AND DYNAMIC LINEAR MODELS
- Partial non-Gaussian state space
- On Gibbs sampling for state space models
- Likelihood analysis of non-Gaussian measurement time series
- BAYESIAN ANALYSIS OF ECONOMETRIC TIME SERIES MODELS USING HYBRID INTEGRATION RULES
- The simulation smoother for time series models
- An adaptive resampling scheme for cycle estimation
- Monte Carlo Smoothing for Nonlinear Time Series
Related Items (2)
Comparison of classical and Bayesian approaches for intervention analysis ⋮ Kalman filtering and sequential Bayesian analysis
This page was built for publication: Comparison of sampling schemes for dynamic linear models