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Last update: RNDr. Jitka Zichová, Dr. (23.04.2019)
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Last update: T_KPMS (24.04.2015)
The subject allows students to get acquainted with the statistical analysis of spatial stochastic processes. |
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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. |
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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. |
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Last update: doc. RNDr. Zbyněk Pawlas, Ph.D. (29.09.2021)
Lecture+exercises. |
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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. |
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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. |
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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. |