Least squares estimation of Generalized Space Time AutoRegressive (GSTAR) model and its properties

Budi Nurani Ruchjana*, Svetlana A. Borovkova, H.P. Lopuhaa

*Corresponding author for this work

Research output: Chapter in Book / Report / Conference proceedingConference contributionAcademicpeer-review

Abstract

In this paper we studied a least squares estimation parameters of the Generalized Space Time AutoRegressive (GSTAR) model and its properties, especially in consistency and asymptotic normality. We use R software to estimate the GSTAR parameter and apply the model toward real phenomena of data, such as an oil production data at volcanic layer.

Original languageEnglish
Title of host publication5th International Conference on Research and Education in Mathematics, ICREM5
Pages61-64
Number of pages4
Volume1450
DOIs
Publication statusPublished - 2012
Event5th International Conference on Research and Education in Mathematics, ICREM5 - Bandung, Indonesia
Duration: 22 Oct 201124 Oct 2011

Conference

Conference5th International Conference on Research and Education in Mathematics, ICREM5
CountryIndonesia
CityBandung
Period22/10/1124/10/11

Keywords

  • Asymptotic normal
  • Consistency
  • GSTAR
  • Least squares

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    Ruchjana, B. N., Borovkova, S. A., & Lopuhaa, H. P. (2012). Least squares estimation of Generalized Space Time AutoRegressive (GSTAR) model and its properties. In 5th International Conference on Research and Education in Mathematics, ICREM5 (Vol. 1450, pp. 61-64) https://doi.org/10.1063/1.4724118