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

Budi Nurani Ruchjana | Zendy; Svetlana Borovkova | Zendy; Hendrik P. Lopuhaä | Zendy

AI Assistant Blog Pricing

Home ZAIA Blog

Open Access

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

Author(s) -

Budi Nurani Ruchjana,

Svetlana Borovkova,

Hendrik P. Lopuhaä

Publication year - 2012

Publication title -

aip conference proceedings

Language(s) - English

Resource type - Conference proceedings

SCImago Journal Rank - 0.177

H-Index - 75

eISSN - 1551-7616

pISSN - 0094-243X

DOI - 10.1063/1.4724118

Subject(s) - icon , citation , computer science , autoregressive model , information retrieval , download , search algorithm , space (punctuation) , world wide web , algorithm , mathematics , statistics , programming language , operating system

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

The content you want is available to Zendy users.

Already have an account? Click here to sign in.

Having issues? You can contact us here

Accelerating Research