447-6233-00L  Spatial Statistics

SemesterAutumn Semester 2019
Lecturers
Periodicitytwo-yearly recurring course
CourseDoes not take place this semester.
Language of instructionEnglish
CommentSpecial 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 Link. The Registrar's Office will then register you for the course.



Courses

NumberTitleHoursLecturers
447-6233-00 GSpatial Statistics Special students and auditors need a special permission from the lecturers.
Does not take place this semester.
Block course. For further information see Link
10.5s hrs

Catalogue data

AbstractIn 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.
ObjectiveThe 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.
ContentAfter 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.
Lecture notesSlides, descriptions of the problems for the data analyses and worked-out solutions to them will be provided.
LiteratureP.J. Diggle & P.J. Ribeiro Jr. 2007. Model-based Geostatistics. Springer

Performance assessment

Performance assessment information (valid until the course unit is held again)
Performance assessment as a semester course
ECTS credits1 credit
ExaminersA. J. Papritz
Typeungraded semester performance
Language of examinationEnglish
RepetitionRepetition possible without re-enrolling for the course unit.

Learning materials

No public learning materials available.
Only public learning materials are listed.

Groups

No information on groups available.

Restrictions

General : Special students and auditors need a special permission from the lecturers

Offered in

ProgrammeSectionType
CAS in Applied StatisticsFurther CoursesWInformation
DAS in Applied StatisticsElectivesWInformation
Statistics MasterStatistical and Mathematical CoursesWInformation