Log transformation of variable "income" causes GWR to **** out?

Discussion created by jtimleck on Jun 24, 2011
Latest reply on Apr 27, 2012 by annajane4185
Working on specifying my GWR model and doing my OLS work found, not surprisingly, that "income", and other variables like "population density", and "call_rate" needed transformation. So I used a normal log transformation and computed new field values for each and created "log_income" and "log_pop_density" and "log_call_rate". Before, running the OLS, everything seemed fine. But now, when running GWR, the analysis craps out with the ole...

[INDENT]ERROR 040038: Results cannot be computed because of severe model design problems.
Failed to execute (GeographicallyWeightedRegression).

So I narrowed it down to the "log_income" and "log_pop_density" variables - whenever the "log_income" is included, either as independent or dependent variable, the model completely tanks. For the "log_pop_den" variable only when it's a dependent variable does the model tank. Looking at the distribution graphically (attached) for income it seems OK. Perhaps this isn't the correct (best?) transformation though?

Methodologically I'm working on an city wide grid, measuring about 2000 x 2000 polygons high and wide, each measuring 250' x 250', where almost every one has data within it. I've set bandwidths to extremes, used minimum # of neighbors, AICc, etc. - every iteration possible - and can't seem to get it to fly. Clearly my "transformation" is the problem but not sure what that problem is.

Much thanks for anyone's eyes on this.