In this paper, we built some models of the spatial data, and evaluate those, using the crime data of Kawaguchi city, Saitama prefecture in Japan. Compute the Moran’I statistics of five crime data related to thefts in the city, the value of sneakthief take the aggregation. So, we pay attention to the sneak, and make a model to estimate the incidence of the events. As a regression, we select the old-age index among regional indexes. Applying a simple regression(SR), a spatial autoregressive model(SAR), a geographically weighted regression(GWR) , we evaluate these models. In GWR model, it is interesting that there are some sections in which the sign of the coefficient takes the opposite versus SR and SAR
models. So, stratifying the data by the sign of it, we investigate to data precisely.
spatial autoregressive model
geographically weighted regression