Subjects

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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
4EU+:	no
Virtual mobility / capacity:	no
State of the course:	taught
Language:	English, Czech
Teaching methods:	full-time

Guarantor:	doc. RNDr. Zbyněk Pawlas, Ph.D.
Teacher(s):	doc. RNDr. Jiří Dvořák, Ph.D. 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

Opinion survey results Examination dates WS schedule Noticeboard

Annotation -

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.

Last update: Zichová Jitka, RNDr., Dr. (23.04.2019)

Aim of the course -

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

Last update: T_KPMS (24.04.2015)

Course completion requirements -

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.

Last update: Pawlas Zbyněk, doc. RNDr., Ph.D. (23.09.2020)

Literature -

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.

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

Teaching methods -

Lecture+exercises.

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

Requirements to the exam -

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

Last update: Pawlas Zbyněk, doc. RNDr., Ph.D. (11.10.2017)

Syllabus -

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.

Last update: T_KPMS (24.04.2015)

Entry requirements -

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

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