The subject surveys the theory of random fields, spatial processes, spatial statistics models, and their applications to a wide range of areas, including image analysis and GIS (geographic information system). The subject will cover the methodology and modern developments for spatial-temporal modelling, estimation and prediction, and spectral analysis of spatial … For more content click the Read more button below.
The subject surveys the theory of random fields, spatial processes, spatial statistics models, and their applications to a wide range of areas, including image analysis and GIS (geographic information system). The subject will cover the methodology and modern developments for spatial-temporal modelling, estimation and prediction, and spectral analysis of spatial processes. All the methods presented will be introduced in the context of specific datasets with GRASS and R software.
Capstones provide students with a way of integrating and applying knowledge and skills gained throughout their course.
No
Academic progress review - Schedule A subject
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Subject instances
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Learning resources
Recommended - Book - Analysing spatial point patterns in R.
Title:Analysing spatial point patterns in R.
Resource requirement:Recommended
Author/editor:Baddeley, A.
Year:2008
Publisher:WORKSHOP NOTES, VERSION 3.
Recommended - Book - Applied spatial analysis with R
Title:Applied spatial analysis with R
Resource requirement:Recommended
Author/editor:Bivand, R.S., Pebesma, E. J., Gomez-Rubio, V.
Year:2008
Publisher:SPRINGER.
Recommended - Book - Statistics for spatial data
Title:Statistics for spatial data
Resource requirement:Recommended
Author/editor:Cressie, N.A.C
Year:1993
Publisher:WILEY
Career ready
Work based learning (placement):No
Subject intended learning outcomes
On successful completion you will be able to:
1.
Formulate purposeful questions to explore new statistical ideas and subsequently design valid statistical experiments.
2.
Present clear, well structured proofs of important theoretical statistical model results.
3.
Creatively find solutions to real world problems consistent with those commonly faced by practicing statisticians.
4.
Professionally defend or question the validity of existing statistical analyses and associated evidence-based conclusions that are derived via application of sound spatial statistical methodology.
Enrolment rules
Special conditions
A sufficient background in probability and statistics is required to undertake this subject.
Requisite rules
Prerequisites: STA3AS or STA4AS and (STA3SI or STM3SI) or (STA4SI or STM4SI) or enrolment into SMDS
