A Periodic State Space Model to Monthly Long-term Temperature Data
| Data(s) |
05/07/2016
05/07/2016
01/06/2016
|
|---|---|
| Resumo |
This work presents a periodic state space model to model monthly temperature data. Additionally, some issues are discussed, as the parameter estimation or the Kalman filter recursions adapted to a periodic model. This framework is applied to monthly long-term temperature time series of Lisbon. |
| Identificador |
978-84-608-8178-0 |
| Idioma(s) |
eng |
| Relação |
biometria.sgapeio.es/ |
| Direitos |
openAccess |
| Palavras-Chave | #State space model #Kalman filter #periodic data #monthly temperature |
| Tipo |
conferenceObject |
