# Module ST3454: Stochastic Models in Space and Time II

**Credit weighting (ECTS)**- 5 credits
**Semester/term taught**- Hilary term 2012-13
**Contact Hours**- 11 weeks, 3 lectures including tutorials per week
**Lecturer**- Associate Professor Rozenn Dahyot
**Learning Outcomes**- On successful completion of this module students should be able to
- Define and describe the different methods introduced in the course;
- Program, analyse and select the best model;
- Interpret output of data analysis performed by a computer statistics package;

**Module Content**-
- Kalman Filter;
- State Space Models;
- Brownian motion;
- Orntein-Uhlenbeck Process;
- Dirac function;
- Kriging;
- Spectral analysis;
- Radon transform;
- Functional data analysis (Kernel density estimates, Nadaraya-Watson estimator)

**Module Prerequisite**- Solid knowledge in mathematics and statistics required e.g. on Linear algebra, Integration and differentiation, expectation operator.
**Recommended Reading**-
*Linear Models for Multivariate, Time Series, and Spatial Data*, R.Christensen, Springer 1991;*Multivariate Geostatistics - An Introduction with Applications*, H.Wackernagel, Springer 2003*Statistics of Spatial Data*, Noel Cressie, Wiley 1993*Geostatistics for Environmental Scientists*, R. Webster and M.A. Oliver, John Wiley and Sons 2001*Time series Analysis with Applications in R*, J.D. Cryer and K.S. Chan, Springer 2008*Functional Data Analysis*, J.O. Ramsay and B.W. Silverman, Springer 2006

**Assessment Detail**

This module will be examined jointly with ST3453
in a 3-hour **examination** in Trinity term,
except that those taking just one of the
two modules will have a 2 hour examination.