Jurnal Ilmu Dasar
Vol 9 No 1 (2008)

Statistical Inference for Modeling Neural Network in Multivariate Time Series

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

Article Info

Publish Date
15 Jan 2008

Abstract

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.

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Journal Info
Jurnal Ilmu Dasar
Website

Abbrev

JID

Publisher

Universitas Jember

Subject

Control & Systems Engineering Mathematics

Description

Jurnal ILMU DASAR (JID) is a national peer-reviewed and open access journal that publishes research papers encompasses all aspects of natural sciences including Mathematics, Physics, Chemistry and Biology. JID publishes 2 issues in 1 volume per year. First published, volume 1 issue 1, in January ...