Statistical Learning in Genetics

Daniel Sorensen holds PhD and DSc degrees from the University of Edinburgh and is an elected Fellow of the American Statistical Association. He was professor of Statistical Genetics at Aarhus University where, at present, he is professor emeritus.

• - 1. Overview. - Part I Fitting Likelihood and Bayesian Models. - 2. Likelihood. - 3. Computing the Likelihood. - 4. Bayesian Methods. - 5. McMC in Practice. - Part II Prediction. - 6. Fundamentals of Prediction. - 7. Shrinkage Methods. - 8. Digression on Multiple Testing: False Discovery Rates. - 9. Binary Data. - 10. Bayesian Prediction and Model Checking. - 11. Nonparametric Methods: A Selected Overview. - Part III Exercises and Solutions. - 12. Exercises. - 13. Solution to Exercises.