Analysis Methods

Analysis Method Tutorials

We should aim at having each person do at least one tutorial. Please choose from the list below or add an item as you see fit (email Xiao Jin). The goal is for the presentation to be fairly in-depth and not just a description of the topic. Things we’d like to see are e.g., 1) advantages/disadvantages of the method, 2) when/where/why it works/does not work, 3) theoretical background, 4) implementation issues, 5) description of a toy experiment that uses the technique successfully (this can be, for example, reporting some preliminary results using your research data).

1. Principal/independent component analysis,
2. Multidimensional scaling
3. Self-organizing maps
4. Hidden Markov models
5. Detrended cross-correlation analysis
6. Functional data analysis
7. Relevance vector machines
8. Neural networks
9. Associate naive Bayes classifier
10. Linear discriminant analysis
11. classical change point detection