VVZ API is not affiliated with ETH Zurich. Data might be outdated or incorrect. Please view the official ETHZ Vorlesungsverzeichnis for binding information.

447-6233-00L 1 Credits MSC , WBZ D-MATH
You're viewing possible stale or outdated data. Please check the latest semester for more up-to-date information.

Spatial Statistics

Lecturers & Examiners: Dr. Andreas Jürg Papritz
Special Students "University of Zurich (UZH)" in the Master Program in Biostatistics at UZH cannot register for this course unit electronically. Forward the lecturer's written permission to attend to the Registrar's Office. Alternatively, the lecturer may also send an email directly to . The Registrar's Office will then register you for the course.
VVZ CR n/a

Last Updated: 2026-02-05 15:34:48

Abstract

In many research fields, spatially referenced data are collected. When analysing such data the focus is either on exploring their structure (dependence on explanatory variables, autocorrelation) and/or on spatial prediction. The course provides an introduction to geostatistical methods that are useful for such purposes.

Objective

The course will provide an overview of the basic concepts and stochastic models that are commonly used to model spatial data. In addition, the participants will learn a number of geostatistical techniques and acquire some familiarity with software that is useful for analysing spatial data.

Content

After an introductory discussion of the types of problems and the kind of data that arise in environmental research, an introduction into linear geostatistics (models: stationary and intrinsic random processes, modelling large-scale spatial patterns by regression, modelling autocorrelation by variogram; kriging: mean-square prediction of spatial data) will be taught. The lectures will be complemented by data analyses that the participants have to do themselves.

Resources

Lecture Notes

Slides, descriptions of the problems for the data analyses and worked-out solutions to them will be provided.

Literature

P.J. Diggle & P.J. Ribeiro Jr. 2007. Model-based Geostatistics. Springer

General Information

Language
English
Levels
MSC , WBZ
Frequency
Every two years

Examination

Type
ungraded semester performance
Performance assessment on 8 February 2021.

Course Components

Type Title Time & Place Hours
lecture with exercise Spatial Statistics
Block course on 11, 18, 25 January 2021. For further information see
  • 11.01 Date 14:00-18:00 (ON LI NE)
  • 18.01 Date 14:00-18:00 (ON LI NE)
  • 25.01 Date 14:00-18:00 (ON LI NE)
10.5 h semesterly

Offered In