This article is concerned with a dynamic factor model for spatio- temporal environmental variables. The model is proposed in a state-space formulation which, through the Kalman recursions, allows a unified approach to prediction and estimation. Full probabilistic inference for the model parameters is facilitated by adapting standard Markov chain Monte Carlo (MCMC) algorithms for dynamic linear models to our model formulation.
(2011). Spatial dynamic factor models with environmental applications [conference presentation - intervento a convegno]. Retrieved from http://hdl.handle.net/10446/26753
Spatial dynamic factor models with environmental applications
2011-01-01
Abstract
This article is concerned with a dynamic factor model for spatio- temporal environmental variables. The model is proposed in a state-space formulation which, through the Kalman recursions, allows a unified approach to prediction and estimation. Full probabilistic inference for the model parameters is facilitated by adapting standard Markov chain Monte Carlo (MCMC) algorithms for dynamic linear models to our model formulation.File allegato/i alla scheda:
| File | Dimensione del file | Formato | |
|---|---|---|---|
|
112.pdf
accesso aperto
Descrizione: publisher's version - versione dell'editore
Dimensione del file
82.98 kB
Formato
Adobe PDF
|
82.98 kB | Adobe PDF | Visualizza/Apri |
Pubblicazioni consigliate
Aisberg ©2008 Servizi bibliotecari, Università degli studi di Bergamo | Terms of use/Condizioni di utilizzo
