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The formulation of structural time series models in discrete and continuous time
| dc.contributor.advisor | Structural time series model |
| dc.contributor.author | Harvey, A. C. |
| dc.date.accessioned | 2008-03-07T10:29:16Z |
| dc.date.available | 2008-03-07T10:29:16Z |
| dc.date.issued | 1983-12 |
| dc.identifier.issn | 0210-8054 (versió paper) |
| dc.identifier.uri | http://hdl.handle.net/2099/4515 |
| dc.description.abstract | This paper sets out an approach for modelling univariate time series, including those in which observations are available on a daily basis. An underlying continuous time model is formulated and it is shown that this model has important implications for the way in which a discrete model is set up. It is also shown that the continuous time model allows observations subject to temporal aggregation and irregularly spaced observations to be handled relatively easily. The extension to cases where explanatory variables are to be included in the model is also discussed. |
| dc.format.extent | p. 563-575 |
| dc.language.iso | eng |
| dc.publisher | Universitat Politècnica de Barcelona. Centre de Càlcul |
| dc.relation.ispartof | Qüestiió. 1983, vol.7, núm.4 |
| dc.rights | Attribution-NonCommercial-NoDerivs 2.5 Spain |
| dc.rights.uri | http://creativecommons.org/licenses/by-nc-nd/2.5/es/ |
| dc.subject.other | Inference |
| dc.subject.other | Continuous time models |
| dc.subject.other | Daily observations |
| dc.subject.other | Forecasting |
| dc.subject.other | Irregular observations |
| dc.subject.other | Kalman filter |
| dc.subject.other | Continuous time model |
| dc.title | The formulation of structural time series models in discrete and continuous time |
| dc.type | Article |
| dc.subject.lemac | Inferència |
| dc.subject.lemac | Processos estocàstics |
| dc.subject.ams | Classificació AMS::62 Statistics::62M Inference from stochastic processes |
| dc.rights.access | Open Access |
| local.ordre | 6 |
