Pemodelan Time Series Multivariat secara Automatis  

Oleh:

Halim, Siana ; Chandra, Arif

Jenis: Article from Journal - ilmiah nasional - terakreditasi DIKTI - non-atma jaya
Dalam koleksi: Jurnal Teknik Industri vol. 13 no. 1 (Jun. 2011), page 19-26.
Topik: Multivariate time series; VAR; SVAR; VECM; SVEC
Fulltext: 18150-20840-2-PB.pdf (269.99KB)

Isi artikel

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.

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