Current information:This item will be continuously updated during the course.
- I wish all the students welcome to the first lecture at 15.15 on January 16, 2018 in E:C.
- (18/1) It is now possible to sign up for the first computer session. When you sign up here you also form the groups for the home assignment. This is done by clicking here.
- (27/1) It is now possible to sign up for the second computer session. This is done by clicking here.
- (5/2) It is now possible to sign up for the third computer session. This is done by clicking here.
- (12/2) It is now possible to sign up for the fourth computer session. This is done by clicking here.
- (19/2) It is now possible to sign up for the fifth computer session. This is done by clicking here.
- (20/2) It is now possible to sign up for the Oral exam. This is done by clicking here.
- (22/2) It is now possible to sign up for the sixth computer session. This is done by clicking here.
Tuesdays 15-17, E:C
Thursdays 10-12, E:1406 (reading week 1)
Thursdays 8-10, E:1406 (reading week 2-7)
See also the schedule below
Computer sessions for projects: (Reading week 2--7)
Wednesdays in E:Neptunus, E:Pluto choose either 8-10 or 15-17. Sign up link available above (from reading week 1).
(Reading week 2--7)
Friday 15:30-16:30, MH:130 (MW), MH:138A (MJ) and MH:326 (SW)
Three home assignments/projects and an oral exam after the last project.
The assignments will be handed out during the 2nd, 4th, and 6th course week.
The Questions for the oral exam are now available here.
|Day||Lectures (chapters in the book)||Home assignments|
|w1||Tue||16/1||L1||Introduction, the Monte Carlo (MC) method (1, 6.1)|
R. Echhardt (1987) Stan Ulam, John von Neumann, and the Monte Carlo method
Rules for Canfield Solitaire
|Thu||18/1||L2||MC (cont.), Random number generation (6.1-6.2) |
How things are done in MATLAB
Uniform random numbers pre v. 5
Random Number Generators: Good Ones Are Hard To Find, Parker and Miller (1998)
Ziggurat algorithm for Gaussian distribution Mersenne twister article C-code Mersenne twister
Proof of inversemethod pdf
|w2||Tue||23/1||L3||MC (cont.), random number generation (cont.) (6.4.1)||HA1 out(HA1, powercurve)||L3 pdf|
|Thu||25/1||L4||Random number generation (cont.), variance reduction (6.4.2-6.4.3)||L4 pdf|
|w3||Tue||30/1||L5||Sequential Monte Carlo (SMC) methods (6.3)||L5 pdf|
|Thu||1/2||L6||SMC methods (cont.)||L6 pdf|
|w4||Tue||6/2||L7||SMC methods (cont.) |
A key paper on SMC: Gordon et al. (1993)
|HA1 in (6/2 15:00)
HA2 out pdf
|Thu||8/2||L8||Markov chain Monte Carlo (MCMC) (7)|
Two key papers on MCMC: Metropolis et al. (1953)
|w5||Tue||13/2||L9||MCMC (7.1)||L9 pdf
Part of proof of LLN pdf
Some implementation tips for MCMC Metropolis-Hastings samplers: MH_tips
|w6||Tue||20/2||L11||Stochastic modelling and Bayesian inference, |
MCMC for Bayesian computation (7.2-7.3)
|HA2 in (20/2 15:00)
HA3 out pdf
Data and files for HA3 coal_mine_disasters.mat,atlantic.txt,est_gumbel.m
|Thu||22/2||L12||Statistical models||L12 pdf|
|w7||Tue||27/2||L13||Bootstrap (9) |
A leisurely look at the Bootstrap, the Jackknife,
and Cross-Validation (1983)
|Thu||1/3||L14||Bootstrap (cont), Permutation tests (9.8)||L14 pdf|
|w8||Tue||6/3||HA3 in (6/3 15:00)|
Geof H. Givens and Jennifer A. Hoeting Computational Statistics
Second Edition (2012)
The course book is now available as an ebook: Computational Statistics by Geof H. Givens and Jennifer A. Hoeting
You can also look at the Book homepage to download the data used in the book.
The above book is the only one needed for the course.
However if you wish to explore other literature some good options are:
- Markov Chain Monte Carlo in Practice, Gilks, Richardson and Spiegelhalter, 1996
- Monte Carlo Statistical Methods, Robert and Casella, 2005
- Bootstrap Methods and Their Application, Davison and Hinkley, 1997
- An Introduction to the Bootstrap, Efron and Tibshirani, 1994
Course administrator/lecturer:Magnus Wiktorsson
phone: 046-222 86 25
Computer sessions:Maria Juhlin
phone: 046-222 79 83