TITLE

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

AUTHOR(S)
Ruchjana, Budi Nurani; Borovkova, Svetlana A.; Lopuhaa, H. P.
PUB. DATE
May 2012
SOURCE
AIP Conference Proceedings;5/22/2012, Vol. 1450 Issue 1, p61
SOURCE TYPE
Academic Journal
DOC. TYPE
Article
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.
ACCESSION #
75526982

 

Related Articles

  • Estimation and testing of higher-order spatial autoregressive panel data error component models. Badinger, Harald; Egger, Peter // Journal of Geographical Systems;Oct2013, Vol. 15 Issue 4, p453 

    This paper develops an estimator for higher-order spatial autoregressive panel data error component models with spatial autoregressive disturbances, SARAR( R, S). We derive the moment conditions and optimal weighting matrix without distributional assumptions for a generalized moments (GM)...

  • ON PARAMETER ESTIMATION IN THE BASS MODEL BY NONLINEAR LEAST SQUARES FITTING THE ADOPTION CURVE. MARKOVIC, DARIJA; JUKIĆ, DRAGAN // International Journal of Applied Mathematics & Computer Science;Mar2013, Vol. 23 Issue 1, p145 

    The Bass model is one of the most well-known and widely used first-purchase diffusion models in marketing research. Estimation of its parameters has been approached in the literature by various techniques. In this paper, we consider the parameter estimation approach for the Bass model based on...

  • Novel Procedure for Characterizing Nonlinear Systems with Memory and Combating the Curse of Dimensionality. Nuttall, A. H.; Katz, R. A.; Hughes, D. R.; Koch, R. M. // AIP Conference Proceedings;2015, Vol. 1685 Issue 1, p1 

    A well-known mathematical model for characterizing nonlinear systems was originally proposed by Vito Volterra (1860- 1940) and later developed by Norbert Wiener (1894-1964). More recently, Albert Nuttall, working with coauthors, has made substantial improvements to Wiener's approach, in which...

  • Least-Squares Parameter Estimation Algorithm for a Class of Input Nonlinear Systems. Weili Xiong; Wei Fan; Rui Ding // Journal of Applied Mathematics;2012, p1 

    This paper studies least-squares parameter estimation algorithms for input nonlinear systems, including the input nonlinear controlled autoregressive (IN-CAR) model and the input nonlinear controlled autoregressive autoregressive moving average (IN-CARARMA) model. The basic idea is to obtain...

  • A least squares method for spectral analysis of space-time series. Wu, Dong L.; Hays, Paul B. // Journal of the Atmospheric Sciences;10/15/95, Vol. 52 Issue 20, p3501 

    Describes the application of a least-squares fitting method for a space-time Fourier analysis of the High Resolution Doppler Imager (HRDI) on board the Upper Atmosphere Research Satellite (UARS). Resolution of space-time spectra; Handling of irregular cases; Examination of various sampling...

  • Equalities between OLSE, BLUE and BLUP in the linear model. Haslett, Stephen; Isotalo, Jarkko; Liu, Yonghui; Puntanen, Simo // Statistical Papers;May2014, Vol. 55 Issue 2, p543 

    We consider equalities between the ordinary least squares estimator ( $$\mathrm {OLSE} $$), the best linear unbiased estimator ( $$\mathrm {BLUE} $$) and the best linear unbiased predictor ( $$\mathrm {BLUP} $$) in the general linear model $$\{ \mathbf y , \mathbf X \varvec{\beta }, \mathbf V...

  • R-Norm Shannon-Gib bs Type Inequality. Kumar, Satish; Choudhary, Arun // Journal of Applied Sciences;2011, Vol. 11 Issue 15, p2866 

    In this study, we study one parametric generalization measure of H (P) and H (P; Q). For the measure H (P; Q) we give three different kind of generalizations. These generalizations are R-Norm entropy and R-Norm inaccuracies. The Shannon-Gibbs type inequality has been generalized in different way...

  • Threshold selection for extremes under a semiparametric model. Gonzalez, Juan; Rodriguez, Daniela; Sued, Mariela // Statistical Methods & Applications;Nov2013, Vol. 22 Issue 4, p481 

    In this work we propose a semiparametric likelihood procedure for the threshold selection for extreme values. This is achieved under a semiparametric model, which assumes there is a threshold above which the excess distribution belongs to the generalized Pareto family. The motivation of our...

  • A new noise-compensated estimation scheme for multichannel autoregressive signals from noisy observations. Xiaomei Qu; Jie Zhou; Yingting Luo // Journal of Supercomputing;Oct2011, Vol. 58 Issue 1, p34 

    In many engineering applications concerning the recovery of signals from noisy observations, a common approach consists in adopting autoregressive (AR) models. This paper is concerned with not only the estimation of multichannel autoregressive (MAR) model parameters but also the recovery of...

Share

Read the Article

Courtesy of VIRGINIA BEACH PUBLIC LIBRARY AND SYSTEM

Sorry, but this item is not currently available from your library.

Try another library?
Sign out of this library

Other Topics