Pemodelan Time Series Multivariat secara Automatis

Pemodelan Time Series Multivariat secara Automatis

This research aims at establishing model of multivariate time series by means of econometric instruments. Four instruments in use are vector auto regressive (VAR), structural vector auto regressive (SVAR), vector error correction model (VECM), and structural vector error correction (SVEC). VAR and V...

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Main Authors: Siana Halim, Arif Chandra
Format: Article
Language:English
Published: Petra Christian University 2011-01-01
Series:Jurnal Teknik Industri
Subjects:
Multivariate time series
VAR
SVAR
VECM
SVEC
Online Access:http://puslit2.petra.ac.id/ejournal/index.php/ind/article/view/18150
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spelling doaj-e9c57f42e9994461b8b99226ce76114a2020-11-24T21:49:19ZengPetra Christian UniversityJurnal Teknik Industri1411-24852011-01-011311926Pemodelan Time Series Multivariat secara AutomatisSiana HalimArif ChandraThis research aims at establishing model of multivariate time series by means of econometric instruments. Four instruments in use are vector auto regressive (VAR), structural vector auto regressive (SVAR), vector error correction model (VECM), and structural vector error correction (SVEC). VAR and VECM are employed to estimate and construct models and, subsequently, predict the future values of an object. SVAR and SVEC serve to analyze innovative structures of a model. VAR and SVAR can be implemented only to stationary data whilst VECM and SVEC can be applied to non-stationary inputs. The identification and estimation of the model in this research are specifically designed by R software. Based on this software, all the aforestated models are conclusively able to identify dynamic relationship of endogenous variabel in a model well. http://puslit2.petra.ac.id/ejournal/index.php/ind/article/view/18150Multivariate time seriesVARSVARVECMSVEC
collection DOAJ
language English
format Article
sources DOAJ
author Siana Halim
Arif Chandra
spellingShingle Siana Halim
Arif Chandra
Pemodelan Time Series Multivariat secara Automatis
Jurnal Teknik Industri
Multivariate time series
VAR
SVAR
VECM
SVEC
author_facet Siana Halim
Arif Chandra
author_sort Siana Halim
title Pemodelan Time Series Multivariat secara Automatis
title_short Pemodelan Time Series Multivariat secara Automatis
title_full Pemodelan Time Series Multivariat secara Automatis
title_fullStr Pemodelan Time Series Multivariat secara Automatis
title_full_unstemmed Pemodelan Time Series Multivariat secara Automatis
title_sort pemodelan time series multivariat secara automatis
publisher Petra Christian University
series Jurnal Teknik Industri
issn 1411-2485
publishDate 2011-01-01
description This research aims at establishing model of multivariate time series by means of econometric instruments. Four instruments in use are vector auto regressive (VAR), structural vector auto regressive (SVAR), vector error correction model (VECM), and structural vector error correction (SVEC). VAR and VECM are employed to estimate and construct models and, subsequently, predict the future values of an object. SVAR and SVEC serve to analyze innovative structures of a model. VAR and SVAR can be implemented only to stationary data whilst VECM and SVEC can be applied to non-stationary inputs. The identification and estimation of the model in this research are specifically designed by R software. Based on this software, all the aforestated models are conclusively able to identify dynamic relationship of endogenous variabel in a model well.
topic Multivariate time series
VAR
SVAR
VECM
SVEC
url http://puslit2.petra.ac.id/ejournal/index.php/ind/article/view/18150
work_keys_str_mv AT sianahalim pemodelantimeseriesmultivariatsecaraautomatis
AT arifchandra pemodelantimeseriesmultivariatsecaraautomatis
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