Tapis kalman ruang waktu=Space time Kalman filter
Many physical or biological processes involve variability over both space and time. A large datas,et and the modelling of space, time, and spatio-temporal interaction cause traditional space time methods are limited. This paper presents an approach to space time prediction that achieves dimension re...
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| Format: | Article |
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[Yogyakarta] : Universitas Gadjah Mada
2005
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| _version_ | 1826031201004027904 |
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| author | Perpustakaan UGM, i-lib |
| author_facet | Perpustakaan UGM, i-lib |
| author_sort | Perpustakaan UGM, i-lib |
| collection | UGM |
| description | Many physical or biological processes involve variability over both space and time. A large datas,et and the modelling of space, time, and spatio-temporal interaction cause traditional space time methods are limited. This paper presents an approach to space time prediction that achieves dimension reduction and uses a statistical model that is temporally dynamic and spatially descriptive, called space time Kalman filter. The model also
allows a non dinamic spatial component.
Key Words : prediction, filter, optimal prediction, Bayesian inference, orthonormal basis. |
| first_indexed | 2024-03-13T18:34:43Z |
| format | Article |
| id | oai:generic.eprints.org:18021 |
| institution | Universiti Gadjah Mada |
| last_indexed | 2024-03-13T18:34:43Z |
| publishDate | 2005 |
| publisher | [Yogyakarta] : Universitas Gadjah Mada |
| record_format | dspace |
| spelling | oai:generic.eprints.org:180212014-06-18T00:27:35Z https://repository.ugm.ac.id/18021/ Tapis kalman ruang waktu=Space time Kalman filter Perpustakaan UGM, i-lib Jurnal i-lib UGM Many physical or biological processes involve variability over both space and time. A large datas,et and the modelling of space, time, and spatio-temporal interaction cause traditional space time methods are limited. This paper presents an approach to space time prediction that achieves dimension reduction and uses a statistical model that is temporally dynamic and spatially descriptive, called space time Kalman filter. The model also allows a non dinamic spatial component. Key Words : prediction, filter, optimal prediction, Bayesian inference, orthonormal basis. [Yogyakarta] : Universitas Gadjah Mada 2005 Article NonPeerReviewed Perpustakaan UGM, i-lib (2005) Tapis kalman ruang waktu=Space time Kalman filter. Jurnal i-lib UGM. http://i-lib.ugm.ac.id/jurnal/download.php?dataId=796 |
| spellingShingle | Jurnal i-lib UGM Perpustakaan UGM, i-lib Tapis kalman ruang waktu=Space time Kalman filter |
| title | Tapis kalman ruang waktu=Space time Kalman filter |
| title_full | Tapis kalman ruang waktu=Space time Kalman filter |
| title_fullStr | Tapis kalman ruang waktu=Space time Kalman filter |
| title_full_unstemmed | Tapis kalman ruang waktu=Space time Kalman filter |
| title_short | Tapis kalman ruang waktu=Space time Kalman filter |
| title_sort | tapis kalman ruang waktu space time kalman filter |
| topic | Jurnal i-lib UGM |
| work_keys_str_mv | AT perpustakaanugmilib tapiskalmanruangwaktuspacetimekalmanfilter |