Сравнение на методи
Прегледайте избраните методи един до друг; редовете с разлики са откроени.
| Модел с Байесови фиксирани ефекти× | Байесова ОЛС (Байесова обикновена най-малка квадратична регресия)× | |
|---|---|---|
| Област | Иконометрия | Иконометрия |
| Семейство | Regression model | Regression model |
| Година на възникване≠ | 2000–2008 | 1971 |
| Създател≠ | Chib (2008); Lancaster (2000) | Arnold Zellner |
| Тип≠ | Bayesian panel regression | Bayesian linear regression |
| Основополагащ източник≠ | Lancaster, T. (2000). The incidental parameter problem since 1948. Journal of Econometrics, 95(2), 391–413. DOI ↗ | Zellner, A. (1971). An Introduction to Bayesian Inference in Econometrics. Wiley. ISBN: 978-0471169376 |
| Други названия | Bayesian within estimator, Bayesian FE model, Bayesian individual fixed effects, Bayesian least squares dummy variable | Bayesian linear regression, Bayesian normal regression, BLR, Bayesian least squares |
| Свързани | 5 | 5 |
| Резюме≠ | The Bayesian fixed effects model applies Bayesian inference to the classical within-group panel estimator. Unit-specific intercepts capture time-invariant unobserved heterogeneity, while prior distributions on all parameters allow probability statements about coefficients and full uncertainty quantification via the posterior distribution. | Bayesian OLS combines the classical linear regression likelihood with prior distributions over the coefficients and error variance. Rather than reporting point estimates, it produces full posterior distributions that quantify both estimated effects and their uncertainty. The approach is especially valuable when prior knowledge is available or when samples are small. |
| ScholarGateНабор от данни ↗ |
|
|