In the module we will use the statistical computing package R. This program is ... [
2] Maria L. Rizzo, Statistical Computing with R. Chapman & Hall/CRC, 2008.
MATH5835M Statistical Computing General Information http://www1.maths.leeds.ac.uk/~voss/2013/5835M.html Jochen Voss,
[email protected] 2013/14, semester 1
Lectures and Example Classes There will be 27 lectures (L1-L27) and 6 example classes (E1-E6). The schedule is given by the following table. Tue 9-10am 1-2pm Wed 9-10am 10-11am
w1
w2
w3
w4
w5
w6
w7
w8
w9
w10
01.10.
08.10.
15.10.
22.10.
29.10.
05.11.
12.11.
19.11.
26.11.
03.12.
w11 10.12.
— —
L3 E1
— L6
— E2
— L11
— E3
— L16
— E4
— L21
— E5
— L26
02.10.
09.10.
16.10.
23.10.
30.10.
06.11.
13.11.
20.11.
27.11.
04.12.
11.12.
L1 L2
L4 L5
L7 L8
L9 L10
L12 L13
L14 L15
L17 L18
L19 L20
L22 L23
L24 L25
L27 E6
The lectures will take place in Roger Stevens LT 07 (Tuesdays) and Roger Stevens LT 09 (Wednesdays). Software In the module we will use the statistical computing package R. This program is free software, you can download it from the project homepage http://www.r-project.org/ . It will be your own responsibility to learn R (but of course we are happy to help if you get stuck). The MATH5838M homepage (see the link above) contains links to some useful resources. Assessment Practical (30%), 2.5 hour exam (70%). The practical will cover the computational parts of the module. You will need to tackle programming tasks (using R), and to present the results in a written report. The exam will assess the theoretical parts of the module. References The module is self-contained, i.e. you should be able to follow the lectures without refering to additional sources. In case you want to do further reading, a good source is the following book, which was specially written for the module: [1] J. Voss, An Introduction to Statistical Computing: A Simulation-based Approach. Wiley, 2014. More in-depth information, beyond what we will be able to cover in the lectures, is for example contained in the following texts. [2] Maria L. Rizzo, Statistical Computing with R. Chapman & Hall/CRC, 2008. [3] B. D. Ripley, Stochastic Simulation. Wiley, 1987. [4] C. P. Robert and G. Casella, Monte Carlo statistical methods. Springer, 2004. [5] W. R. Gilks, S. Richardson and D. J. Spiegelhalter, Markov chain Monte Carlo in practice. Chapman & Hall/CRC, 1995. Finally, most topics covered can also be found in the old MATH5835M lecture notes from 2011/12 (slightly different from this year’s syllabus): [6] http://www1.maths.leeds.ac.uk/~voss/2011/5835/notes.pdf
