Pooyan Amir-Ahmadi
Datos Biográficos
| ID | 8920184 |
|---|---|
| NOMBRE | Pooyan Amir-Ahmadi |
| NOMBRES | Pooyan |
| APELLIDO | Amir-Ahmadi |
| FIRMA | AMIR-AHMADI P |
| AFILIACIONES | Department of Economics, University of Illinois at Urbana-Champaign, Urbana, IL 61820 () |
| VERIFICADO | No |
| TOTAL DE OBRAS | 1 |
| TOTAL DE CITAS | 0 |
| OBRAS COMO AUTOR | 1 |
| OBRAS COMO EDITOR | 0 |
| PRIMER AÑO DE PUBLICACIÓN | 2020 |
| AÑO MÁS RECIENTE DE PUBLICACIÓN | 2020 |
| ÍNDICE H | 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…
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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 obra) · Bayesian inference (1 obra) · Bayesian probability (1 obra) · Computer Science (1 obra) · Covariance (1 obra) · Econometrics (1 obra) · Financial Risk and Volatility Modeling (1 obra) · Forecasting Techniques and Applications (1 obra) · Hyperparameter (1 obra) · Machine learning (1 obra)