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http://hdl.handle.net/1942/8967
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DC Field | Value | Language |
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dc.contributor.advisor | MOLENBERGHS, Geert | - |
dc.contributor.advisor | CORTINAS ABRAHANTES, Jose | - |
dc.contributor.author | WOUTERS, Kristien | - |
dc.date.accessioned | 2008-12-03T19:16:12Z | - |
dc.date.available | 2008-12-03T19:16:12Z | - |
dc.date.issued | 2008 | - |
dc.identifier.uri | http://hdl.handle.net/1942/8967 | - |
dc.description.abstract | In this thesis, we have focussed on the classification of multiple class, multivariate longitudinal data. This research was driven by a study conducted to classify psychotropic drugs based on electro-encephalogram or EEG data. For each of the compound-by-dose combinations in the five psychotropic drug classes, data on the sleep-wake behaviour of rats were collected during a 16 hours period. The sleepwake behaviour was summarized into six standard sleep-wake stages, resulting in a six-variate longitudinal profile per rat. From a statistical point of view, analyzing EEG data poses important challenge, because of the high-dimensionality and the longitudinal character of the data. The longitudinal profiles are usually highly irregular and the variability between and within subjects are relatively high. | - |
dc.language.iso | en | - |
dc.publisher | UHasselt Diepenbeek | - |
dc.title | Classification methods multi-class multivariate longitudinal data | - |
dc.type | Theses and Dissertations | - |
local.format.pages | 166 | - |
local.bibliographicCitation.jcat | T1 | - |
local.type.refereed | Non-Refereed | - |
local.type.specified | Phd thesis | - |
dc.bibliographicCitation.oldjcat | D1 | - |
item.fulltext | With Fulltext | - |
item.accessRights | Open Access | - |
item.fullcitation | WOUTERS, Kristien (2008) Classification methods multi-class multivariate longitudinal data. | - |
item.contributor | WOUTERS, Kristien | - |
Appears in Collections: | PhD theses Research publications |
Files in This Item:
File | Description | Size | Format | |
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Kristien Wouters.pdf | 1.69 MB | Adobe PDF | View/Open |
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