Pemodelan time series multivariat secara automatis

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.

Siana Halim Unknown Universitas Kristen Petra Indonesian eDIMENSI Journal Unknown Jurnal Teknik Industri, Vol. 13, No. 1, Juni 2011, 19-26; Siana Halim (94-032) Unknown

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