Research Article Open Access

MAXIMUM LIKELIHOOD ESTIMATION FOR SPATIAL DURBIN MODEL

Rokhana Dwi Bekti1, Anita Rahayu1 and Sutikno2
  • 1 Bina Nusantara University, Indonesia
  • 2 , Indonesia

Abstract

Spatial Durbin Model (SDM) is one method of spatial autoregressive. This model was developed because the dependencies in the spatial relationships not only occur in the dependent variable, but also on the independent variables. In the assessment of parameter estimation, the process is carried out by Maximum Likelihood Estimation (MLE). This estimation can be approximation by Spatial Autoregressive Models (SAR). By MLE, the matrix of independent variable in SAR is X and in SDM is [I X W1X], so that the estimation in SDM was done by replace matrix X in SAR by [I X W1X]. This estimation perform the unbiased estimator for β and σ2. Estimate ρ was done by optimize the concentrated log-likelihood function with respect to ρ.

Journal of Mathematics and Statistics
Volume 9 No. 3, 2013, 169-174

DOI: https://doi.org/10.3844/jmssp.2013.169.174

Submitted On: 19 March 2013 Published On: 15 June 2013

How to Cite: Bekti, R. D., Rahayu, A. & Sutikno, (2013). MAXIMUM LIKELIHOOD ESTIMATION FOR SPATIAL DURBIN MODEL. Journal of Mathematics and Statistics, 9(3), 169-174. https://doi.org/10.3844/jmssp.2013.169.174

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Keywords

  • Maximum Likelihood Estimation
  • Spatial Autoregressive Models
  • Spatial Durbin Model