Journal of Mathematical and Fundamental Sciences
Vol. 49 No. 2 (2017)

Error Assumptions on Generalized STAR Model

Yundari Yundari (Statistics Research Division, Faculty of Mathematics and Natural Sciences, Institut Teknologi Bandung, Jalan Ganesha 10, Bandung 40132)
Udjianna Sekteria Pasaribu (Statistics Research Division, Faculty of Mathematics and Natural Sciences, Institut Teknologi Bandung, Jalan Ganesha 10, Bandung 40132)
Utriweni Mukhaiyar (Statistics Research Division, Faculty of Mathematics and Natural Sciences, Institut Teknologi Bandung, Jalan Ganesha 10, Bandung 40132)

Article Info

Publish Date
03 Oct 2017

Abstract

For GSTAR models, the least squares estimation method is commonly used since errors are assumed be uncorrelated. However, this method is not appropriate when errors are correlated, either in time or spatially. For these cases, the generalized least squares (GLS) method can be applied. GLS is more powerful since it has an error parameter that can act as a controller of the model to produce an efficient estimator. In this study, R Software was used to estimate GSTAR parameters. The resulted model was applied to real data, i.e. the monthly tea production of five plantations in West Java, Indonesia. The best model for forecasting was the GSTAR(1;1) model with temporally correlated error assumption.

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Journal Info
Journal of Mathematical and Fundamental Sciences
Website

Abbrev

jmfs

Publisher

Institut Teknologi Bandung

Subject

Astronomy Chemistry Earth & Planetary Sciences Mathematics Physics

Description

Journal of Mathematical and Fundamental Sciences welcomes full research articles in the area of Mathematics and Natural Sciences from the following subject areas: Astronomy, Chemistry, Earth Sciences (Geodesy, Geology, Geophysics, Oceanography, Meteorology), Life Sciences (Agriculture, Biochemistry, ...