文章基本信息

标题：APLIKASI GENERALIZED SPACE TIME AUTOREGRESSIVE (GSTAR) PADA PEMODELAN VOLUME KENDARAAN MASUK TOL SEMARANG
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作者：Dian Anggraeni ; Alan Prahutama ; Shofi Andari 等
期刊名称：MEDIA STATISTIKA
印刷版ISSN：1979-3693
电子版ISSN：2477-0647
出版年度：2013
卷号：6
期号：2
页码：61-70
语种：English
出版社：MEDIA STATISTIKA
摘要：Time series data from neighboring separated location often associated both spatially and through time. Generalized space time autoregrresive (GSTAR) model is one of the most common used space-time model to modeling and predicting spatial and time series data. This study applied GSTAR to modeling vehicle volume entering four tollgate (GT) in Semarang City: GT Muktiharjo, GT Gayamsari, GT Tembalang, and GT Manyaran. The data was collected by month from 2003 to 2009. The best model provided by this study is GSTAR (2 1 )-I(1,12) uniformly weighted with the smallest REMSE mean 76834. Key words: GSTAR, Vehicle Volume, Space-Time Model