Coding week #4

mehaksachdeva
Published: 06/25/2019

What did I do this week?

This week I tested the Poisson MGWR model using a simulated dataset with three cases - single independent variable, multiple independent variables and a global model to check with the Poisson global model. The tests performed as expected and the results were all as expected. The scores for AIC, AICc and BIC were a little different from what was expected, but after testing it was realized that the simulated data was not the best use-case for a multiple bandwidth test case. I also tried the Binomial MGWR model this week. Though it ran without errors and converged, the results are not as expected. This model needs further exploration and resolution of a few outstanding tasks. I opened a Pull request for the simulated data example for Poisson MGWR (https://github.com/pysal/mgwr/pull/56 ) and for the code base changes to accommodate these models (https://github.com/pysal/mgwr/pull/57 ).

What is coming up next?

In the coming week I will work on testing the Binomial MGWR model and resolve the issues in the results. I will also plan for the next part of the project which is to enable predictions from the model at unsampled locations and think about how to introduce that functionality.

Did I get stuck anywhere?

No major issues were encountered in testing the Poisson model using simulated data this week. The results were as expected and comparable to the GWR and global models. The Binomial MGWR model still needs further work and resolution of some issues.

Looking forward to the progress update next week!

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