ST453      Half Unit
Probability and Mathematical Statistics II

This information is for the 2019/20 session.

Teacher responsible

Prof Konstantinos Kardaras

Availability

This course is available on the MSc in Quantitative Methods for Risk Management. This course is available with permission as an outside option to students on other programmes where regulations permit.

Pre-requisites

Probability and Mathematical Statistics I is a pre-requisite.

Course content

This course provides instruction in advanced topics in probability and mathematical statistics, mainly based on

martingale theory. It is a continuation of  Probability and Mathematical Statistics I. The following topics will in particular be covered:

  1. Conditional expectation revisited; linear regression; martingales and first examples.
  2. Concentration inequalities; dimension reduction; log-Sobolev inequalities.
  3. Martingale transforms; optional sampling theorem; convergence theorems.
  4. Sequential testing; backwards martingales; law of large numbers; de Finetti’s theorem.
  5. Markov chains; recurrence; reversibility; foundations of MCMC.
  6. Ergodic theory.
  7. Brownian motion; quadratic variation; stochastic integration.
  8. Stochastic differential equations; diffusions; filtering.
  9. Bayesian updating; Ergodic diffusions; Langevin samplers.
  10. Brownian bridge; empirical processes; Kolmogorov-Smirnov statistic.

Teaching

20 hours of lectures and 10 hours of seminars in the LT.

Week 6 is Reading Week.

Formative coursework

Students will be expected to produce 9 problem sets in the LT.

Weekly problem sets that are discussed in subsequent seminars. The coursework that will be used for summative assessment will be chosen from a subset of these problems.

Indicative reading

  1. Williams, D. (1991). Probability with Martingales. Cambridge University Press.
  2. Durrett, R. (2019). Probability: Theory and Examples. Cambridge Series in Statistical and Probabilistic Mathematics.
  3. Karatzas, I, Shreve S. (1991). Brownian motion and Stochastic Calculus. Springer GTM.
  4. Shao, J. (2007). Mathematical Statistics. Springer Texts in Statistics.
  5. Keener, R. (2010). Theoretical Statistics. Springer Texts in Statistics.

Assessment

Exam (70%, duration: 2 hours, reading time: 10 minutes) in the summer exam period.
Coursework (30%) in the LT.

Three of the homework problem sets will be submitted and marked as assessed coursework.

Key facts

Department: Statistics

Total students 2018/19: Unavailable

Average class size 2018/19: Unavailable

Controlled access 2018/19: No

Value: Half Unit

Guidelines for interpreting course guide information

Personal development skills

  • Problem solving
  • Application of numeracy skills
  • Specialist skills