- Instructor: James MacKinnon
- Office: Dunning 236
- Office Hours:
- There are no specific office hours. If you just have a brief question, feel free to pop into my office whenever my door is open. For anything that is likely to take some time, please make an appointment by sending me an e-mail (jgm [AT] econ.queensu.ca).
- Classes: MC A516, Tuesday 10:00-11:20, Thursday 10:00-11:20
ECON 950 is an advanced course on econometric theory and methods. The course will deal with a variety of methods that are often referred to collectively as "machine learning" or "statistical learning".
Much of the course will be based on the book
Trevor Hastie, Robert Tibshirani, and Jerome Friedman, "Elements of Statistical Learning," Second Edition, Springer, 2009.
Another very useful book, which is more specialized, more up to date, and in places more technical, is:
Trevor Hastie, Robert Tibshirani, and Martin Wainwright, "Statistical Learning with Sparsity," CRC Press, 2015.
A less advanced book, which contains a lot of useful R code, is
Gareth James, Daniela Witten, Trevor Hastie, and Robert Tibshirani, "An Introduction to Statistical Learning," Springer, 2014.
Every registered student must make two presentations. The first presentation will involve discussing one or more articles or book chapters, either theoretical or empirical. The second will present a preliminary version of the student's own work, which will ultimately become an essay to satisfy the requirements of the course.
Auditors must make one presentation, which will involve discussing one or more articles or book chapters.
The lecture notes will, eventually, be posted here:
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Failure to abide by these conditions is a breach of copyright, and it may also constitute a breach of academic integrity under the University Senate's Academic Integrity Policy Statement.
Last updated on January 3, 2019.