Random numbers, optimization methods, Markov processes, Monte Carlo methods and stochastic calculus and differential equations, survey of real world examples of stochastic methods.
FSK3898 Stochastic Methods 5.0 credits
This course has been discontinued.
Last planned examination: Autumn 2022
Decision to discontinue this course:
No information inserted
Course offerings are missing for current or upcoming semesters.
Headings with content from the Course syllabus FSK3898 (Autumn 2018–) are denoted with an asterisk ( )
Content and learning outcomes
Course contents
Intended learning outcomes
After completing the course, you should be able to:
- List examples of different stochastic methods and judge when the methods are applicable.
- Explain the physical principles and background of Monte Carlo methods and stochastic calculus.
- Illustrate and discuss how Monte Carlo methods are constructed.
Literature and preparations
Specific prerequisites
Enrolled as PhD student.
Ph. D students in computational sciences and e-science.
Basic knowledge in statistics and probability theory and basic knowledge using Matlab/Octave.
Recommended knowledge: Basic courses in programming, matematical statistics and probability theory.
Recommended prerequisites
No information inserted
Equipment
Laptop with Matlab (or Octave) installed.
Literature
C. Gardiner, Stochastic Methods- A handbook for the Natural and Social Sciences , Springer Verlag 2009, ISBN: 978-3-540-70712-7
J. C. Spall, Introduction to Stochastic Search and Optimization, Wiley 2003, ISBN: 978-0-471-33052-3
N. G. van Kampen, Stochastic Processes in Physics and Chemistry, Elsevier, ISBN:978-0-444-52965-7
Examination and completion
If the course is discontinued, students may request to be examined during the following two academic years.
Grading scale
G
Examination
- LAB1 - Computer exercises, 1.5 credits, grading scale: G
- PRO1 - Project work, 3.5 credits, grading scale: G
Based on recommendation from KTH’s coordinator for disabilities, the examiner will decide how to adapt an examination for students with documented disability.
The examiner may apply another examination format when re-examining individual students.
DAT1: Computer exercises, 1.5 hp credits, grade scale: P/F
PRO1: Project work, 3.5 hp credits, grade scale: P/F
Other requirements for final grade
Examination (pass/fail):
* Passing computer exercises
* Project work with oral and written presentation
Opportunity to complete the requirements via supplementary examination
No information inserted
Opportunity to raise an approved grade via renewed examination
No information inserted
Examiner
Ethical approach
- All members of a group are responsible for the group's work.
- In any assessment, every student shall honestly disclose any help received and sources used.
- In an oral assessment, every student shall be able to present and answer questions about the entire assignment and solution.
Further information
Course room in Canvas
Registered students find further information about the implementation of the course in the course room in Canvas. A link to the course room can be found under the tab Studies in the Personal menu at the start of the course.
Offered by
Main field of study
This course does not belong to any Main field of study.
Education cycle
Third cycle
Add-on studies
No information inserted
Contact
Lars Bergqvist (lbergqv@kth.se)