Vol 9 No 1 (2008)

Statistical Inference for Modeling Neural Network in Multivariate Time Series

Urwatul Wutsqa, Dhoriva (Unknown)
Subanar, Subanar (Unknown)
Guritno, Suryo (Unknown)
Soejoeti, Zanzawi (Unknown)

Article Info

Publish Date
15 Jan 2008


We present a statistical procedure based on hypothesis test to build neural networks model in multivariate time series case. The method involved strategies for specifying the number of hidden units and the input variables in the model using inference of R2 increment. We draw on forward approach starting from empty model to gain the optimal neural networks model. The empirical study was employed relied on simulation data to examine the effectiveness of inference procedure. The result showed that the statistical inference could be applied successfully for modeling neural networks in multivariate time series analysis.

Copyrights © 2008

Journal Info





Biochemistry, Genetics & Molecular Biology Chemistry Mathematics Physics


Jurnal ILMU DASAR (JID) adalah jurnal ilmiah yang melingkupi bidang matematika, fisika, kimia dan biologi. Naskah yang diusulkan untuk diterbitkan Jurnal Ilmu Dasar adalah naskah yang belum pernah diterbitkan dan atau tidak sedang dipertimbangkan penerbitannya di majalah lain. Jurnal Ilmu Dasar ...