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

Budi Nurani Ruchjana; Svetlana A. Borovkova; H.P. Lopuhaa

doi:10.1063/1.4724118

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

Finance

Research output: Chapter in Book / Report / Conference proceeding › Conference contribution › Academic › peer-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 language	English
Title of host publication	5th International Conference on Research and Education in Mathematics, ICREM5
Pages	61-64
Number of pages	4
Volume	1450
DOIs	https://doi.org/10.1063/1.4724118
Publication status	Published - 2012
Event	5th International Conference on Research and Education in Mathematics, ICREM5 - Bandung, Indonesia Duration: 22 Oct 2011 → 24 Oct 2011

Conference

Conference	5th International Conference on Research and Education in Mathematics, ICREM5
Country/Territory	Indonesia
City	Bandung
Period	22/10/11 → 24/10/11

Keywords

Asymptotic normal
Consistency
GSTAR
Least squares

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10.1063/1.4724118

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title = "Least squares estimation of Generalized Space Time AutoRegressive (GSTAR) model and its properties",

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.",

keywords = "Asymptotic normal, Consistency, GSTAR, Least squares",

author = "Ruchjana, {Budi Nurani} and Borovkova, {Svetlana A.} and H.P. Lopuhaa",

year = "2012",

doi = "10.1063/1.4724118",

language = "English",

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volume = "1450",

pages = "61--64",

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note = "5th International Conference on Research and Education in Mathematics, ICREM5 ; Conference date: 22-10-2011 Through 24-10-2011",

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Ruchjana, BN, Borovkova, SA & Lopuhaa, HP 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, 5th International Conference on Research and Education in Mathematics, ICREM5, Bandung, Indonesia, 22/10/11. https://doi.org/10.1063/1.4724118

Least squares estimation of Generalized Space Time AutoRegressive (GSTAR) model and its properties. / Ruchjana, Budi Nurani; Borovkova, Svetlana A.; Lopuhaa, H.P.
5th International Conference on Research and Education in Mathematics, ICREM5. Vol. 1450 2012. p. 61-64.

Research output: Chapter in Book / Report / Conference proceeding › Conference contribution › Academic › peer-review

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AU - Borovkova, Svetlana A.

AU - Lopuhaa, H.P.

PY - 2012

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AB - 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.

KW - Asymptotic normal

KW - Consistency

KW - GSTAR

KW - Least squares

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ER -

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

Abstract

Conference

Keywords

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