TMA4250 - Spatial Statistics


Examination arrangement

Examination arrangement: Portfolio assessment
Grade: Letters

Evaluation Weighting Duration Grade deviation Examination aids
Arbeider 30/100
Skriftlig eksamen 70/100 4 timer

Course content

Parameter estimation, simulation and applications of Gaussian random fields, point fields and
discrete Markov random fields. Examples from image analysis, and environmental and natural
resource applications.

Learning outcome

1. Knowledge. The student has knowledge about basic concepts of the theory about Gaussian random fields, including spatial interpolation by various types of kriging, and algorithms for unconditional and conditional simulation. The student has also knowledge about basic
concepts of the theory of point random fields, including K- and L-statistics, spatial Poisson, Cox and hard-core fields, and simulation of such point fields. Moreover, the student has knowledge about basic concepts of the theory of discrete Markov random fields, including
simulation of Markov random fields by MCMC algorithms. Lastly, the student has knowledge of parameter estimation in spatial random fields.

2. Skills. The student can formulate statistical models for simple spatial phenomena, and perform parameter estimation under these models by use of suitable computer software. Moreover, the student can evaluate conditional models by stochastic simulation.

Learning methods and activities

Lectures and works (projects). Portfolio assessment is the basis for the grade awarded in the course. This portfolio comprises a written final examination (70%) and works (projects) (30%). The results for the constituent parts are
to be given in %-points, while the grade for the whole portfolio (course grade) is given by the letter grading system. Retake of examination may be given as an oral examination. The lectures may be given in English. If the course is taught in English, the exam may be given only in English. Students are free to choose Norwegian or English for written assessments.

Compulsory assignments

  • Work

Specific conditions

Compulsory activities from previous semester may be approved by the department.

Course materials

Will be announced at the start of the course.

Credit reductions

Course code Reduction From To
SIF5064 7.5

Version: 1
Credits:  7.5 SP
Study level: Second degree level


Term no.: 1
Teaching semester:  SPRING 2017

Language of instruction: English, Norwegian


Subject area(s)
  • Statistics
  • Technological subjects
Contact information
Course coordinator:

Department with academic responsibility
Department of Mathematical Sciences


Examination arrangement: Portfolio assessment

Term Status code Evaluation Weighting Examination aids Date Time Examination system Room *
Spring ORD Arbeider 30/100
Room Building Number of candidates
Spring ORD Skriftlig eksamen 70/100 2017-06-02 09:00
Room Building Number of candidates
Summer KONT Arbeider 30/100
Room Building Number of candidates
Summer KONT Skriftlig eksamen 70/100
Room Building Number of candidates
  • * The location (room) for a written examination is published 3 days before examination date. If more than one room is listed, you will find your room at Studentweb.

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