The comparative investigation of GWR and OLS methods in estimation of location models

Using the quantitative tools, methods and techniques in various sciences has been expanded during the recent years. The quantitative methods’ utilization in different branches of Humanities, especially the urban and regional planning have been always faced to various challenges. The reason of generated challenges is the complex nature of the human behaviors. Ordinary least Squares (OLS) is one of the popular methods in spatial model domain. It is supposed, in this method, that there is no spatial anisotropy among the observations and the spatial dependence doesn’t exist among the noise terms. It can be seen, in spatial data, using of the general regression methods such as Ordinary Least Squares (OLS) and will cause the model parameter dispersion. So it is necessary to use some other spatial modelling methods such as Geographically Weighted Regression (GWR). The experimental studies, have been done in this domain, reveal that the spatial regression methods can consider the spatial anisotropy among the observations and the noise terms dependence and will cause the estimations without the swearing and compatible with the parameters of the statistical society .