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Part A Statistical Programming

Hilary Term 2017

Course Material




Part C and MSc Graphical Models

Michaelmas Term 2016

Course Material




MSc Statistical Methods
Log-Linear Models and Contingency Tables

Hilary Term 2016

Course Material




MSc R Programming

Michaelmas Term 2014

Course Material




CDT Module 1: Statistical Computing

Module Outline

Michaelmas Term 2014

We will be using the statistical software package R, which you can get here. Please install it on your own computer and practice using it as early as possible.

Notes

R Questions Review Sheet (Solutions)

Talk Slides

Numerical Issues and Computing

Slides on Bayesian Computing

Adaptive MCMC Slides (Krys Latuszynski)

Lauritzen and Spiegelhalter (1998) (Robin Evans)

Intractable Likelihoods MCMC (Matti Vihola)

Lasso (Francois Caron)

Scaling in MCMC (Gareth Roberts)

Statistical Challenges in fMRI (Thomas Nichols)

Notes on R

  1. Some Points About Functions

  2. Profiling

  3. Speeding Up Code I

  4. Speeding Up Code II

  5. Calling External Code

  6. Debugging

  7. Writing R Packages

Vignettes

Here's an example vignette file and a BibTeX file. It generates a vignette which looks something like this.

Adding Vignettes to Your Package

Resources

Hadley Wickham's Advanced R book is highly recommended, and his (not yet complete) book on R packages is also good.

The R Inferno takes a detailed look at some of R's quirks.




Causal Inference with Counterfactuals

Graduate Lectures, Hilary Term 2014

Some brief lecture notes.

A blog post which covers some of the philosophy.