Bayesian Forecasting and Dynamic Models
This text is concerned with Bayesian learning, inference and forecasting in dynamic environments. We describe the structure and theory of classes of dynamic models and their uses in forecasting and time series analysis. The principles, models and methods of Bayesian forecasting and time - ries analy...
| Main Authors: | West, Mike (Author), Harrison, Jeff (Author) |
|---|---|
| Corporate Author: | SpringerLink (Online service) |
| Format: | Electronic eBook |
| Language: | English |
| Published: |
New York, NY :
Springer New York,
1997.
|
| Edition: | Second Edition. |
| Series: | Springer Series in Statistics,
|
| Subjects: | |
| Online Access: | Full Text via HEAL-Link |
Similar Items
-
Forecasting with Exponential Smoothing The State Space Approach /
by: Hyndman, Rob, et al.
Published: (2008) -
Stochastic Models with Power-Law Tails The Equation X = AX + B /
by: Buraczewski, Dariusz, et al.
Published: (2016) -
Applied Multivariate Statistical Analysis
by: Härdle, Wolfgang, et al.
Published: (2007) -
Lévy Matters IV Estimation for Discretely Observed Lévy Processes /
by: Belomestny, Denis, et al.
Published: (2015) -
Linear Models and Generalizations Least Squares and Alternatives /
by: Rao, C. Radhakrishna, et al.
Published: (2008)