semipar

Projects I've done during the 'Semiparametric regression' course conducted by Jaroslaw Harezlak, PhD at the Faculty of Mathematics and Computer Science, University of Wrocław.

Course syllabus

1. Introduction to semiparametric regression.
2. Linear regression methods review.
3. Introduction to smoothing.
4. Linear mixed models.
5. Smoothing parameter selection.
6. Linear mixed models and reml.
7. Confidence intervals, confidence bands and hypothesis testing.
8. Simple semiparametric models.
9. Additive models.
10. Semiparametric mixed models.
11. Interaction models.
12. Introduction to generalized linear models (GLM).
13. Generalized additive models.
14. Bivariate and spatial smoothing.
15. Measurement error models.

Implementation

We used R during the course.

License

Distributed under the GNU GPLv3 license. See LICENSE for more information.

Contributing

I believe any contributions to this project do not make sense, however feel free to use my code.