Lecture slides on Generalized Linear and Additive models

I gave a lecture yesterday as part of Chris’ computational neuroscience class on generalized linear and additive models (GLMs and GAMs) and their application to neuroscience. A lot of the people in the class have little to no background in stats so I kept it very basic. I also have exercises involving the estimation of a place field from simulated that borrow heavily from Dr. Paninski’s assignment for his neural data analysis class (he himself inherited them from Uri Eden). Email me if you need the .m files that go with the assignment for a class or for practice.

Lecture slides

Assignment


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