Dynamic shrinkage priors for large time-varying parameter regressions using scalable Markov Chain Monte Carlo Methods
Year of publication: |
[2023]
|
---|---|
Authors: | Hauzenberger, Niko ; Huber, Florian ; Koop, Gary |
Publisher: |
Glasgow : Department of Economics, University of Strathclyde |
Subject: | Time-varying parameter regression | dynamic shrinkage prior | global-local shrinkage prior | Bayesian variable selection | scalable Markov Chain Monte Carlo | Markov-Kette | Markov chain | Monte-Carlo-Simulation | Monte Carlo simulation | Bayes-Statistik | Bayesian inference | Schätztheorie | Estimation theory | Schätzung | Estimation | Regressionsanalyse | Regression analysis |
-
Hauzenberger, Niko, (2024)
-
Bayesian model averaging and principal component regression forecasts in a data rich environment
Ouysse, Rachida, (2016)
-
Semiparametric GARCH via Bayesian model averaging
Chen, Wilson Ye, (2021)
- More ...
-
Predictive density combination using a tree-based synthesis function
Chernis, Tony, (2023)
-
Macroeconomic forecasting using BVARs
Hauzenberger, Niko, (2024)
-
Predictive density combination using a tree-based synthesis function
Chernis, Tony, (2023)
- More ...