SubjectsSubjects(version: 941)
Course, academic year 2023/2024
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Spatial Statistics - NMST543
Title: Prostorová statistika
Guaranteed by: Department of Probability and Mathematical Statistics (32-KPMS)
Faculty: Faculty of Mathematics and Physics
Actual: from 2022
Semester: winter
E-Credits: 5
Hours per week, examination: winter s.:2/2, C+Ex [HT]
Capacity: unlimited
Min. number of students: unlimited
Virtual mobility / capacity: no
State of the course: taught
Language: English, Czech
Teaching methods: full-time
Teaching methods: full-time
Guarantor: doc. RNDr. Zbyněk Pawlas, Ph.D.
Class: M Mgr. PMSE
M Mgr. PMSE > Povinně volitelné
Classification: Mathematics > Probability and Statistics
Pre-requisite : NMTP438
Is interchangeable with: NSTP154
Annotation -
Last update: RNDr. Jitka Zichová, Dr. (23.04.2019)
The course is a continuation of Spatial Modelling NMTP438. The main attention is devoted to the statistical techniques for point processes, including both inhomogeneous point processes and marked point processes. The course also deals with geostatistics and statistics for areal data.
Aim of the course -
Last update: T_KPMS (24.04.2015)

The subject allows students to get acquainted with the statistical analysis of spatial stochastic processes.

Course completion requirements -
Last update: doc. RNDr. Zbyněk Pawlas, Ph.D. (23.09.2020)

The course is finalized by a credit from exercise class and by a final exam.

The credit from exercise class is necessary for taking part in the final exam.

Requirements for receiving the credit from exercise class: active participation, short individual project.

Attempt to receive the credit from exercise class cannot be repeated.

Literature -
Last update: doc. RNDr. Zbyněk Pawlas, Ph.D. (28.10.2019)

Cressie N.A.C.: Statistics for Spatial Data. Wiley, 1993.

Illian J., Penttinen A., Stoyan H., Stoyan D.: Statistical Analysis and Modelling of Spatial Point Patterns. Wiley, 2008.

Moller J., Waagepetersen R. P.: Statistical Inference and Simulation for Spatial Point Processes. Chapman&Hall/CRC, 2003.

Schabenberger O., Gotway C.: Statistical Models for Spatial Data Analysis. Chapman&Hall/CRC, 2005.

Teaching methods -
Last update: doc. RNDr. Zbyněk Pawlas, Ph.D. (29.09.2021)


Requirements to the exam -
Last update: doc. RNDr. Zbyněk Pawlas, Ph.D. (11.10.2017)

The final exam is oral. All material covered during the course may be part of the exam.

Syllabus -
Last update: T_KPMS (24.04.2015)

1. Statistics of point processes, estimation of characteristics, hypothesis testing, model parameter estimation.

2. Statistics of marked point processes, estimation of characteristics, tests of independence.

3. Geostatistics, estimation of variogram, kriging.

4. Areal data, parameter estimation, spatial autocorrelation tests.

Entry requirements -
Last update: doc. RNDr. Zbyněk Pawlas, Ph.D. (18.05.2018)

Knowledge of material covered in Spatial Modelling NMTP438: spatial models on lattices, random fields, random measures, point processes, marked point processes.

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