Application of Spatial Error Model For Ordinary And Fuzzy Data With Comparison

In this paper, an application of spatial data (ordinary & fuzzy) was studied by using a spatial regression model, which is the spatial error model (SEM), data used are 38 location for several Iraqi cities. In this study estimated parameter’s model by ordinary least squares OLS and maximum likelihood MLE method for (ordinary and fuzzy data) then applied Simulation method to ensure the performance of the methods for estimating the model that used in our study, accordingly a program was designed in Matlab language , included the generation of data with different sample sizes (n =50, 100) default values for the parameters model, the spatial dependence parameter and a spatial weights matrix was used according the Rook Contiguity. After repeating the experiment 1000 times and comparison through statistical criteria (RMSE) the simulation results showed that the spatial error model for fuzzy data is better than the spatial error model for ordinary data.