MATH48121/MATH68121 Computationally Intensive Statistics 2009/2010

Lectures
Reading List
Lecture Notes
Theoretical Exercises
Example Sheets
Problem Sheets
Past Exam Paper
Data Sets

Lecture:

Lecture Times: Tuesday 11-12. Alan Turing G.108
Friday 9-10. Alan Turing G.209
Computer Lab: Tuesday 2-4. Alan Turing G.105

Reading List:

For full syllabus: Syllabus


Lecture Notes:

Section 1. Introduction
Section 2. Simulation Lecture Notes
Section 3. Non-parametric Lecture Notes
Section 4. EM Lecture Notes
Section 5. MCMC Lecture Notes
Gibbs Sampler
Metropolis-Hastings algorithm

Theoretical Exercises:

Section 2. Simulation Exercises and solutions
Section 3. Non-parametric Exercises and solutions
Section 4. EM Exercises and solutions
Section 5. MCMC Exercises and solutions

Example Sheets:

Introduction to R lecture.
Example Sheet 0 and Solutions 0

Example Sheet 1 and Solutions 1
Example Sheet 2 and Solutions 2
Example Sheet 3 and Solutions 3
Example Sheet 4 and Solutions 4
Example Sheet 5 and Solutions 5
Example Sheet 6 and Solutions 6
Example Sheet 7 and Solutions 7
Example Sheet 8 and Solutions 8
Example Sheet 9 and Solutions 9
Example Sheet 10 and Solutions 10

Problem Sheets:

Introduction to R coursework. (MSc students only.)
Coursework and Coursework Solutions

Problem Sheet 1 and Solutions 1
Problem Sheet 2 and Solutions 2
Problem Sheet 3 and Solutions 3
Problem Sheet 4 and Solutions 4
Problem Sheet 5 and Solutions 5
Problem Sheet 6 and Solutions 6
Problem Sheet 7 and Solutions 7
Problem Sheet 8 and Solutions 8
Problem Sheet 9 and Solutions 9
Problem Sheet 10 and Solutions 10

Past Exam Papers:

2005 Exam Paper
2006 Exam Paper
2007 Exam Paper
2008 Exam Paper

Data Sets:

Angina (Problem Sheet 10)
Asthma
Bulb
censored Gamma data (EM Section 4.4)
coal (MCMC Section 5.9)
Diabetes
hierarchical Normal
hierarchical Poisson (Problem Sheet 8)
law
law82
lumber (Problem Sheet 9)
lutenhorm
mcycle
mousec
mouset
wine
wood