This page contains the program of the course. Other information, such as learning outcomes, teachers, literature and examination, can be found in a separate course PM.

Program

Literature

We have the following books and acronyms:

• MvL: Theory of Spatial Statistics: A Concise Introduction, M.N.M. van Lieshout (found here)
• BC: Foundations of Computational Imaging: A Model-Based Approach, C. A. Bouman (found here)
• LN: Lecture notes Statistics of Imaging, M. Rudemo (found here)

Other relevant literature (which might be used in the course):

• HS: Handbook of spatial statistics, Gelfand, Diggle, Guttorp & Fuentes (found here)
• EL: The Elements of Statistical Learning, Hastie, Tibshirani & Friedman (found here)
• GH: Image Analysis for the Biological Sciences, Glasbey & Horgan (found here)

Note that all literature is freely available via the Chalmers library for registered students.

If you want to recap some basic probability and statistics notions, you may e.g. consult Section 2 and 3 of the book by Bouman (BC).

Examination and projects

The examination consists of two parts: 

• A group-based project assignment. Grade: Pass/Fail.
• A written exam on June 3 2026, 14:00-18:00. Allowed exam aids: Chalmers approved calculator. Final grade (Chalmers: U-3-4-5; GU: U-G-VG): 3/G: 20 p, 4: 30 p , 5: 40 p, VG: 37.5 p, max: 50 p.

To pass the course, a student has to pass both the project part and the written exam. The final grade (Chalmers: U-3-4-5; GU: U-G-VG) on the course is based on the exam, which is individual.

The deadlines for the projects can be found at the end of this page under Course summary. All assignments should be uploaded under Canvas/Assignments.  

The exact dates, times and places for the (re)exams can be found on the student portal.

Project details:

The project work is done in groups of 1-3 students - please create a project group as early as possible (go to People and then to Project groups to find the groups). Once you have decided who to be in a group with, make sure that each group member goes to People and then to Project groups to register into the appropriate group slot. If you can not find anybody to be in a group with, please reach out to other people who you see have not yet been registered to a group or to people who are in a group which you see is not yet full - if you are unsuccessful in this endeavour, please reach out to Ottmar and Mathis as soon as possible so that they can help you to find a group to join.

The project involves that the group has to i) hand in a project report and ii) given an oral presentation of the project.  The project has got a slightly new focus compared to previous years.

Each group selects any paper from the journal Spatial Statistics, which you can access via https://www.sciencedirect.com/journal/spatial-statistics (once you are logged in to the Chalmers library). Once you have reached the journal homepage, make searches based on different keywords which interest you (as a group), e.g. geostatistics, random field, point pattern, point process, Gibbs/Markov random field/state, disease mapping, image analysis, etc.

• The choice of paper has to be reported as a Canvas assignment (intended as a check from the course instructors). The deadline for this is deliberately set to after we have covered all the chapters 1-4 in van Lieshout's book.
• The group then reads the selected paper in detail and writes a summary/report on it, which needs to be handed in as a Canvas assignment towards the end of the course (the exact deadline will be found under the appropriate Canvas assignment).
• Each group must also give an oral presentation of its selected paper summary/report; the oral presentation should be planned for 15 minutes. After the presentation, each group gets asked questions for approximately 5 minutes; the course instructors will direct individual questions to the group members.

In summary, the workflow for a student to pass this part of the course, i.e. the project, is that the student: 1) reads and understands the group’s paper, 2) takes part in writing the report, 3) has the group submit the report through Canvas, 4) takes part in putting together and preparing the group’s oral presentation, 5) carries out the oral presentation together with the group members, 6) answers questions directed to the student.

Lectures and Exercises

The schedule of the course is in TimeEdit.

The course typically has two lectures and two computer exercises each week. Details for these are given in the schedule below, which will be updated during the course. For each lecture, the chapters covered in the books will be listed.

The lectures will be given in Euler.

Teachers of the course are Ottmar Cronie (lectures, examiner), ottmar@chalmers.se, and Mathis Rost (lectures, exercises/labs), mathisr@chalmers.se. Lecture notes of the lectures can be found in Files/Lecture notes.

The information below will be updated and extended on an ongoing basis.

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