Modern Regression and Bayesian Methods
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Module Overview: Modern Regression and Bayesian Methods
- Random effects models
- Modern regression (generalised additive models, etc)
- Bayesian methods
- Markov chain Monte Carlo methods
- Case studies
This module is assessed in two assignments. Each is a short project after each block of five lectures. Deadlines will be confirmed in due course.
Basic concepts in
- probability (elementary probability distributions)
- statistics (ideas of estimation, confidence intervals, hypothesis tests)
- linear algebra
In addition, we assume the first semester module 'Regression and Simulation', or its equivalent.