Halim, Siana and CHANDRA, ARIF (2011) Pemodelan Time Series Multivariate secara Automatis. Jurnal Teknik Industri, 13 (1). pp. 19-26. ISSN 1441-2486
![[img]](https://repository.petra.ac.id/style/images/fileicons/application_pdf.png) | PDF Download (269Kb) | |
| PDF (cek plagiasi) Download (184Kb) | Preview | |
| PDF (peerreview) Download (635Kb) | Preview |
Abstract
We constructed an automatic multivariate time series algorithm and implemented that algorithm into R-package. Four instruments in used 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. Based on this package, all the aforestated models are conclusively able to identify dynamic relationship of endogenous variabel in a model well.
| Item Type: | Article |
|---|---|
| Uncontrolled Keywords: | Multivariate time series, VAR, SVAR, VECM, SVEC |
| Subjects: | T Technology > TS Manufactures |
| Divisions: | Faculty of Industrial Technology > Industrial Engineering Department |
| Depositing User: | Admin |
| Date Deposited: | 05 Nov 2012 17:53 |
| Last Modified: | 16 Jan 2019 10:05 |
| URI: | https://repository.petra.ac.id/id/eprint/17804 |
Actions (login required)
| View Item |
