MAXIMUM LIKELIHOOD ESTIMATION FOR SPATIAL DURBIN MODEL
Rokhana Dwi Bekti, Anita Rahayu and Sutikno
DOI : 10.3844/jmssp.2013.169.174
Journal of Mathematics and Statistics
Volume 9, Issue 3
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 ? and ?2. Estimate ? was done by optimize the concentrated log-likelihood function with respect to ?.
© 2013 Rokhana Dwi Bekti, Anita Rahayu and Sutikno . This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.