HETEROSCEDASTICS TIME SERIES MODELLING WITH INTERVENTION AND OUTLIERS FACTOR
Non-stationary time series data is influenced by several factors. The factors reviewed in this study were intervention and outliers. If these two factors have no effect, then heteroscedastic time series modeling and also combined modeling are performed. This research is expected to evaluate the effe...
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id-itb.:477872020-06-21T09:53:27ZHETEROSCEDASTICS TIME SERIES MODELLING WITH INTERVENTION AND OUTLIERS FACTOR Yudistira, Dhika Indonesia Final Project Time series, interventions, outliers, heteroscedastic, and effect. INSTITUT TEKNOLOGI BANDUNG https://digilib.itb.ac.id/gdl/view/47787 Non-stationary time series data is influenced by several factors. The factors reviewed in this study were intervention and outliers. If these two factors have no effect, then heteroscedastic time series modeling and also combined modeling are performed. This research is expected to evaluate the effect of interventions and outliers on time series data categorized as heteroscedastic, so that the effects of both factors can be analyzed. In addition, it also reviewed the duration of the effects of these factors. Outliers or interventions contained in the time series data used, will be associated with real events so that it will produce an interesting story. In addition, the results of this study can also be used as a reference for a related party in making better policies. text |
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Institut Teknologi Bandung |
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Indonesia Indonesia |
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Institut Teknologi Bandung |
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Indonesia |
| description |
Non-stationary time series data is influenced by several factors. The factors reviewed in this study were intervention and outliers. If these two factors have no effect, then heteroscedastic time series modeling and also combined modeling are performed. This research is expected to evaluate the effect of interventions and outliers on time series data categorized as heteroscedastic, so that the effects of both factors can be analyzed. In addition, it also reviewed the duration of the effects of these factors. Outliers or interventions contained in the time series data used, will be associated with real events so that it will produce an interesting story. In addition, the results of this study can also be used as a reference for a related party in making better policies. |
| format |
Final Project |
| author |
Yudistira, Dhika |
| spellingShingle |
Yudistira, Dhika HETEROSCEDASTICS TIME SERIES MODELLING WITH INTERVENTION AND OUTLIERS FACTOR |
| author_facet |
Yudistira, Dhika |
| author_sort |
Yudistira, Dhika |
| title |
HETEROSCEDASTICS TIME SERIES MODELLING WITH INTERVENTION AND OUTLIERS FACTOR |
| title_short |
HETEROSCEDASTICS TIME SERIES MODELLING WITH INTERVENTION AND OUTLIERS FACTOR |
| title_full |
HETEROSCEDASTICS TIME SERIES MODELLING WITH INTERVENTION AND OUTLIERS FACTOR |
| title_fullStr |
HETEROSCEDASTICS TIME SERIES MODELLING WITH INTERVENTION AND OUTLIERS FACTOR |
| title_full_unstemmed |
HETEROSCEDASTICS TIME SERIES MODELLING WITH INTERVENTION AND OUTLIERS FACTOR |
| title_sort |
heteroscedastics time series modelling with intervention and outliers factor |
| url |
https://digilib.itb.ac.id/gdl/view/47787 |
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1822927747902603264 |