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...

Full description

Saved in:

Bibliographic Details
Main Authors:	, ORIEZA FEBRIANDHANI, , Prof. Drs. Subanar, Ph.D
Format:	Theses and Dissertations NonPeerReviewed
Published:	[Yogyakarta] : Universitas Gadjah Mada 2014
Subjects:	ETD
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
Tags:	Add Tag No Tags, Be the first to tag this record!

id	id-ugm-repo.132288
record_format	dspace
spelling	id-ugm-repo.1322882016-03-04T08:05:55Z https://repository.ugm.ac.id/132288/ PENGKLASTERAN DATA RUNTUN WAKTU BERBASIS DENSITAS PERAMALAN , ORIEZA FEBRIANDHANI , Prof. Drs. Subanar, Ph.D ETD 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. [Yogyakarta] : Universitas Gadjah Mada 2014 Thesis NonPeerReviewed , ORIEZA FEBRIANDHANI and , Prof. Drs. Subanar, Ph.D (2014) PENGKLASTERAN DATA RUNTUN WAKTU BERBASIS DENSITAS PERAMALAN. UNSPECIFIED thesis, UNSPECIFIED. http://etd.ugm.ac.id/index.php?mod=penelitian_detail&sub=PenelitianDetail&act=view&typ=html&buku_id=72814
institution	Universitas Gadjah Mada
building	UGM Library
country	Indonesia
collection	Repository Civitas UGM
topic	ETD
spellingShingle	ETD , ORIEZA FEBRIANDHANI , Prof. Drs. Subanar, Ph.D PENGKLASTERAN DATA RUNTUN WAKTU BERBASIS DENSITAS PERAMALAN
description	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.
format	Theses and Dissertations NonPeerReviewed
author	, ORIEZA FEBRIANDHANI , Prof. Drs. Subanar, Ph.D
author_facet	, ORIEZA FEBRIANDHANI , Prof. Drs. Subanar, Ph.D
author_sort	, ORIEZA FEBRIANDHANI
title	PENGKLASTERAN DATA RUNTUN WAKTU BERBASIS DENSITAS PERAMALAN
title_short	PENGKLASTERAN DATA RUNTUN WAKTU BERBASIS DENSITAS PERAMALAN
title_full	PENGKLASTERAN DATA RUNTUN WAKTU BERBASIS DENSITAS PERAMALAN
title_fullStr	PENGKLASTERAN DATA RUNTUN WAKTU BERBASIS DENSITAS PERAMALAN
title_full_unstemmed	PENGKLASTERAN DATA RUNTUN WAKTU BERBASIS DENSITAS PERAMALAN
title_sort	pengklasteran data runtun waktu berbasis densitas peramalan
publisher	[Yogyakarta] : Universitas Gadjah Mada
publishDate	2014
url	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
_version_	1681233475787554816

PENGKLASTERAN DATA RUNTUN WAKTU BERBASIS DENSITAS PERAMALAN

Similar Items