I am modelling count data of migration flow (from origin to destination) with several explanatory variables using negative binomial regression.
Flow from i to j ~ Distance from i to j + socio-economic characteristics at i + socio-economic characteristics at j
I then calculate the residuals and mapped it using the origin and destination spatial units. What does residual map really explain beside over or under predictions? I also did a spatial autocorrelation test of the residual for each map and the result is not significant meaning the distribution of the residuals are random instead of clustering. How can I interpret more?