Coding week #6

mehaksachdeva
Published: 07/11/2019

What did I do this week?

This week I constructed a Monte Carlo experiment design to test the parameters from the Poisson MGWR model. The model was designed to create a random sample for the independent variables, construct dependent variables for Poisson distribution and run the model for 1000 iterations. The results from the experiment were plotted in a notebook and analysed and follow the expected trend. I am maintaining the Pull request for the simulated data example for Poisson MGWR and added the experiment design code to the PR for reference (https://github.com/pysal/mgwr/pull/60 ).

What is coming up next?

In the coming week I will work on testing the Binomial MGWR model with simulated data and finalize the approach for the Binomial model. I will also work on understanding and debugging an issue that is being encountered in the calculation of three performance parameters of the model. It is expected to make the Binomial model convergence simpler too.

Did I get stuck anywhere?

The Monte Carlo design experiment was time consuming and computationally intensive. This issue was resolved using parallel computing techniques that though took a little time to implement, it in turn sped up the process manifold.

Looking forward to the progress update next week!

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