Predicting time-varying parameters with parameter-driven and observation-driven models
Year of publication: |
March 2016
|
---|---|
Authors: | Koopman, Siem Jan ; Lucas, André ; Scharth, Marcel |
Published in: |
The review of economics and statistics. - Cambridge, Mass. : MIT Press, ISSN 0034-6535, ZDB-ID 207962-8. - Vol. 98.2016, 1, p. 97-110
|
Subject: | Zeitreihenanalyse | Time series analysis | Prognoseverfahren | Forecasting model | Monte-Carlo-Simulation | Monte Carlo simulation | Zustandsraummodell | State space model | Theorie | Theory |
-
Time-varying combinations of predictive densities using nonlinear filtering
Billio, Monica, (2013)
-
Non-parametric estimation of forecast distributions in non-Gaussian, non-linear state space models
Ng, Jason, (2013)
-
Predicting time-varying parameters with parameter-driven and observation-driven models
Koopman, Siem Jan, (2012)
- More ...
-
Numerically Accelerated Importance Sampling for Nonlinear Non-Gaussian State Space Models
Koopman, Siem Jan, (2012)
-
Predicting time-varying parameters with parameter-driven and observation-driven models
Koopman, Siem Jan, (2012)
-
Numerically accelerated importance sampling for nonlinear non-Gaussian state space models
Koopman, Siem Jan, (2011)
- More ...