Simple State space models in a mixed model framework
State-space models play a central role in time series analysis. Biological time series, which present trend, seasonal, and cyclic fluctuations, can be well described by such models. In addition, biological experiments and surveys often have a relatively complex design structure calling for special a...
| Main Authors: | , |
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| Format: | Journal Article |
| Language: | Inglés |
| Published: |
Informa UK Limited
2007
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| Subjects: | |
| Online Access: | https://hdl.handle.net/10568/1291 |
| _version_ | 1855526669114146816 |
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| author | Piepho, Hans-Peter Ogutu, Joseph O. |
| author_browse | Ogutu, Joseph O. Piepho, Hans-Peter |
| author_facet | Piepho, Hans-Peter Ogutu, Joseph O. |
| author_sort | Piepho, Hans-Peter |
| collection | Repository of Agricultural Research Outputs (CGSpace) |
| description | State-space models play a central role in time series analysis. Biological time series, which present trend, seasonal, and cyclic fluctuations, can be well described by such models. In addition, biological experiments and surveys often have a relatively complex design structure calling for special attention. It is straightforward to account for design effects in a mixed linear model framework. This article shows how simple state-space models can be cast as a standard mixed model, provided the transition matrix of the state equation has a simple form. This opens up the opportunity for refined modeling of time series data involving complex blocking and treatment structures. Conversely, the state-space model gives rise to a special class of variance-covariance structures. Thus, integrating state-space components into a mixed model broadens the class of variance-covariance structures that may be employed to model serial correlation in longitudinal data. The approach is illustrated using several biological examples. |
| format | Journal Article |
| id | CGSpace1291 |
| institution | CGIAR Consortium |
| language | Inglés |
| publishDate | 2007 |
| publishDateRange | 2007 |
| publishDateSort | 2007 |
| publisher | Informa UK Limited |
| publisherStr | Informa UK Limited |
| record_format | dspace |
| spelling | CGSpace12912024-04-25T06:01:03Z Simple State space models in a mixed model framework Piepho, Hans-Peter Ogutu, Joseph O. models State-space models play a central role in time series analysis. Biological time series, which present trend, seasonal, and cyclic fluctuations, can be well described by such models. In addition, biological experiments and surveys often have a relatively complex design structure calling for special attention. It is straightforward to account for design effects in a mixed linear model framework. This article shows how simple state-space models can be cast as a standard mixed model, provided the transition matrix of the state equation has a simple form. This opens up the opportunity for refined modeling of time series data involving complex blocking and treatment structures. Conversely, the state-space model gives rise to a special class of variance-covariance structures. Thus, integrating state-space components into a mixed model broadens the class of variance-covariance structures that may be employed to model serial correlation in longitudinal data. The approach is illustrated using several biological examples. 2007-08 2010-04-21T10:56:51Z 2010-04-21T10:56:51Z Journal Article https://hdl.handle.net/10568/1291 en Limited Access Informa UK Limited Piepho, H.P.; Ogutu, J.O. 2007. Simple State space models in a mixed model framework. The American Statistician 61(3): 224-232 |
| spellingShingle | models Piepho, Hans-Peter Ogutu, Joseph O. Simple State space models in a mixed model framework |
| title | Simple State space models in a mixed model framework |
| title_full | Simple State space models in a mixed model framework |
| title_fullStr | Simple State space models in a mixed model framework |
| title_full_unstemmed | Simple State space models in a mixed model framework |
| title_short | Simple State space models in a mixed model framework |
| title_sort | simple state space models in a mixed model framework |
| topic | models |
| url | https://hdl.handle.net/10568/1291 |
| work_keys_str_mv | AT piephohanspeter simplestatespacemodelsinamixedmodelframework AT ogutujosepho simplestatespacemodelsinamixedmodelframework |