548-0926/01 – Spatial Statistics (PST)
| Gurantor department | Department of Geoinformatics | Credits | 10 |
| Subject guarantor | prof. Ing. Jiří Horák, Dr. | Subject version guarantor | prof. Ing. Jiří Horák, Dr. |
| Study level | postgraduate | Requirement | Choice-compulsory |
| Year | | Semester | winter + summer |
| | Study language | Czech |
| Year of introduction | 2017/2018 | Year of cancellation | 2022/2023 |
| Intended for the faculties | HGF | Intended for study types | Doctoral |
Subject aims expressed by acquired skills and competences
The objective is to develop student’s knowledge of spatial statistics and increase his/her capability to apply advanced methods of spatial statistics in case studies with topics related to the theme of his/her PhD thesis.
Teaching methods
Lectures
Individual consultations
Summary
The course extends knowledge of spatial statistics. It contains explanation of theoretical models for dot spatial distribution, descriptive and inferentional statistical methods for main geometrical forms of representation of spatial objects with both single and multiple investigated phenomena, methods of hot/cold spot detection, spatial distribution optimization methods, methods of assessment of autocorrelation and anizotropy of spatial data, spatial regression models, multivariate techniques for spatial data and spatio-temporal methods.
Compulsory literature:
Recommended literature:
Additional study materials
Way of continuous check of knowledge in the course of semester
E-learning
Other requirements
No additional requirements are imposed on the student.
Prerequisities
Subject has no prerequisities.
Co-requisities
Subject has no co-requisities.
Subject syllabus:
1. Theoretical types of spatial distribution for events
2. Methods of descriptive statistics for events
3. Inferential statistic methods for 1 type of events (monovariate methods)
4. Inferential statistic methods for more type of events (multivariate methods)
5. Hot spots, cold spots analysis
6. Spatial distribution optimization methods, locational and allocation methods.
7. Gravity theory and application for spatial applications
8. Autocorrelation assesment and anisotropy of spatial data
9. Spatial regression techniques
10. Spatiotemporal prediction
Conditions for subject completion
Occurrence in study plans
Occurrence in special blocks
Assessment of instruction
Předmět neobsahuje žádné hodnocení.