PENGKLASTERAN DATA RUNTUN WAKTU BERBASIS DENSITAS PERAMALAN
A clustering method for time series is introduced, based on probability density of the forecast. First, autoregressive bootstrap procedure combined with nonparametric kernel estimator is applied to data to obtain estimation of the forecast densities. The estimated forecast densities are the used to...
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| Main Authors: | , |
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| Format: | Theses and Dissertations NonPeerReviewed |
| Published: |
[Yogyakarta] : Universitas Gadjah Mada
2014
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| Subjects: | |
| Online Access: | https://repository.ugm.ac.id/132288/ http://etd.ugm.ac.id/index.php?mod=penelitian_detail&sub=PenelitianDetail&act=view&typ=html&buku_id=72814 |
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| Summary: | A clustering method for time series is introduced, based on probability
density of the forecast. First, autoregressive bootstrap procedure combined with
nonparametric kernel estimator is applied to data to obtain estimation of the
forecast densities. The estimated forecast densities are the used to construct the
dissimilarity matrix and hence to perform clustering. Finally, application of this
method in real dataset are discussed. |
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