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 2014 to 2015
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:	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
Incompatibility :	NSTP154
Pre-requisite :	NMTP438
Interchangeability :	NSTP154
Is interchangeable with:	NSTP154

Opinion survey results Examination dates Schedule Noticeboard

Annotation -

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

The course is a continuation of 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.

Literature - Czech

Last update: RNDr. Jitka Zichová, Dr. (05.05.2017)

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.

Teaching methods -

Last update: RNDr. Jiří Dvořák, Ph.D. (28.09.2020)

Lecture+exercises.

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.