Mu-Chun Wang
Biographic Data
| ID | 8920185 |
|---|---|
| NAME | Mu-Chun Wang |
| GIVEN NAMES | Mu-Chun |
| FAMILY NAME | Wang |
| SIGNATURE | WANG M |
| AFFILIATIONS | Universität Hamburg |
| VERIFIED | No |
| TOTAL WORKS | 1 |
| TOTAL CITATIONS | 0 |
| WORKS AS AUTHOR | 1 |
| WORKS AS EDITOR | 0 |
| FIRST PUBLICATION YEAR | 2020 |
| LATEST PUBLICATION YEAR | 2020 |
| H-INDEX | 0 |
Choosing Prior Hyperparameters
Time-varying parameter models with stochastic volatility are widely used to study macroeconomic and financial data. These models are almost exclusively estimated using Bayesian methods. A common practice is to focus on prior distributions that themselves depend on relatively few hyperparameters such as the scaling factor for the prior covariance matrix of the residuals governing time variation in the parameters. The choice of these hyperparameter…
No prominent works on this page.
Choosing Prior Hyperparameters
Time-varying parameter models with stochastic volatility are widely used to study macroeconomic and financial data. These models are almost exclusively estimated using Bayesian methods. A common practice is to focus on prior distributions that themselves depend on relatively few hyperparameters such as the scaling factor for the prior covariance matrix of the residuals governing time variation in the parameters. The choice of these hyperparameter…
Artificial Intelligence (1 work) · Bayesian inference (1 work) · Bayesian probability (1 work) · Computer Science (1 work) · Covariance (1 work) · Econometrics (1 work) · Financial Risk and Volatility Modeling (1 work) · Forecasting Techniques and Applications (1 work) · Hyperparameter (1 work) · Machine learning (1 work)