- Docente: Fedele Pasquale Greco
- Credits: 10
- SSD: SECS-S/01
- Language: Italian
- Moduli: Fedele Pasquale Greco (Modulo 1) Linda Altieri (Modulo 2)
- Teaching Mode: Traditional lectures (Modulo 1) Traditional lectures (Modulo 2)
- Campus: Bologna
- Corso: First cycle degree programme (L) in STATISTICAL SCIENCES (cod. 8054)
Learning outcomes
By the end of the course, the student will be aware of the most basic methods suited for the analysis of environmental phenomena. More specifically, the student will be able to analyse environmental data showing spatial dependence using the statistical software R.
Course contents
Analysiis of areal data:
- Descriptive measures of globale spatial association
-Local Indicators of Spatial Association (LISA)
-Hypothesis testing for global and local spatial association
-Areal data models (CAR and SAR)
-Spatial linear regression
-Spatial smoothing of mortalityrates
Analysiis of geostatistical data:
Geostatistics: descriptive measures of spatial dependence, spatial random fields, variogram, covariogram, kriging.
Analysis of point process data
- Introduction to point processes
- Descriptive measures for point patterns
- Tests for complete spatial randomness
- Interpoint interaction
- Homogeneous Poisson models
- Inhomogeneous Poisson models
- Gibbs processes
- Cox processes
- Marked point processes
- Point process models evaluation
Readings/Bibliography
D. Posa S.De Iaco Geostatistica teoria ed applicazioni. Giappichelli Editore Torino, 2009.
Illian J.B. et al (2008) Statistical Analysis and Modelling of Spatial Point Patterns
Diggle P.J. (2014) Statistical Analysis of Spatial and Spatio-Temporal Point Patterns. Third Edition
Assessment methods
Written and practical exam
Office hours
See the website of Fedele Pasquale Greco
See the website of Linda Altieri