Simulation and Statistical Programming

HT 2019 - Part A - Simulation and Statistical Programming

Lecturers: Prof Geoff Nicholls (Statistical Programming), Prof Julien Berestycki (Simulation)
Class tutors: J. Berestycki / G. Nicholls / A. Caterini
Teaching Assistants: S. Shi

You will find on this webpage the slides and problem sheets regarding the Simulation part of the course. The material regarding Statistical Programming is available from Geoff Nicholls' webpage.

Timetable

Week	Lecture Tuesday 2-3pm LG.01, 24-29 Saint-Giles'	Computer Lab Tue 3-5pm or Fri 9-11am LG.02, 24-29 Saint-Giles'	Problem class Mon. 2pm LG.05 or Thur. 1.30pm LG.04 24-29 Saint-Giles'
1	X	Tue.
2	X	Tue.
3	X	Tue.	X
4	X
5	X	Fri.	X
6	X	Fri.
7	X		X
8	X	Fri.
TT1			X

Simulation lectures

Lecture 1, Introduction and Monte Carlo method
Lecture 2, Inversion method
Lecture 3, Transformation methods
Lecture 4, Rejection sampling
Lecture 5, Importance sampling
Lecture 6, Normalized importance sampling
Lecture 7, Markov chain Monte Carlo
Lecture 8, Metropolis-Hastings algorithm

Download slides: [Part I] [Part II] [Part III]
See also the lecture notes of Geoff Nicholls (HT 2014).
Movie MCMC.
code R for MH image reconstruction.
code R for PS3.

Problem classes

Please hand in the solutions to the problem sheets by Thursday of previous week at 10 and send the R code by email, in a single well-commented R-script to the class TA.

Computer labs

Material on Geoff Nicholls' course page.

Last update: 10 January 2019