Course Syllabus for

Spatial Statistics with Image Analysis
Spatial statistik med bildanalys

FMSN20F, 7.5 credits

Valid from: Autumn 2020
Decided by: Professor Thomas Johansson
Date of establishment: 2020-05-19

General Information

Division: Mathematical Statistics
Course type: Course given jointly for second and third cycle
The course is also given at second-cycle level with course code: FMSN20
Teaching language: English

Aim

The aim of the course is to provide the student with tools for handling high-dimensional statistical problems. The course contains models, and methods with practical applications, mainly for spatial statistics and image analysis. Of special importance are the Bayesian aspects, since they form the foundation for many modern spatial statistical and image analysis methods. The course emphasises methods with appications in climate, environmental statistics, and remote sensing.

Goals

Knowledge and Understanding

For a passing grade the doctoral student must

Competences and Skills

For a passing grade the doctoral student must

Judgement and Approach

For a passing grade the doctoral student must

Course Contents

Bayesian methods for stochastic modelling, classification and reconstruction. Random fields, Gaussian random fields, Kriging, Markov fields, Gaussian Markov random fields, non-Gaussian observationer. Covariance functions, multivariate techniques. Simulation methods for stochastic inference (Gibbs sampling). Applications in climate, environmental statistics, remote sensing, and spatial statistics.

Course Literature

Gelfand, A., Diggle, P. & Guttorp, P.: Handbook of Spatial Statistics. CRC Press Inc, 2010.

Instruction Details

Types of instruction: Lectures, laboratory exercises, project

Examination Details

Examination formats: Written report, seminars given by participants
Grading scale: Failed, pass
Examiner:

Admission Details

Admission requirements: At least one course of FMSF15 Markov processes or FMSF10 Stationary stochastic processes. Matlab proficiency.

Course Occasion Information

Contact and Other Information

Course coordinators:
Web page: www.maths.lth.se/matstat/kurser/fmsn20/


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