Least Squares Estimation of Generalized Space Time AutoRegressive (GSTAR) Model and Its Properties

被引：15
|
作者：
Ruchjana, Budi Nurani [1 ]
Borovkova, Svetlana A. [2 ]
Lopuhaa, H. P. [3 ]
机构：
[1] Padjadjaran State Univ, Dept Math, Fac Math & Nat Sci, Sumedang 45363, Indonesia
[2] Vrije Univ Amsterdam, Fac Econ, Dept Finance, NL-1081 HV Amsterdam, Netherlands
[3] Delft Univ Technol, Delft Inst Appl Math, Fac EEMCS, NL-2628 CD Delft, Netherlands
来源：
5TH INTERNATIONAL CONFERENCE ON RESEARCH AND EDUCATION IN MATHEMATICS (ICREM5) | 2012年 / 1450卷
关键词：
GSTAR; least squares; consistency; asymptotic normal;
D O I：
10.1063/1.4724118
中图分类号：
O29 [应用数学];
学科分类号：
070104 ;
摘要：
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.
引用
收藏
页码：61 / 64
页数：4
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