Point procesess serve as stochastic models for locations of objects that are ran- domly placed in space, e.g. the locations of trees of a given species in a forest stand, earthquake epicenters or defect positions in industrial materials. Stochas- tic reconstruction is an algorithmic procedure providing independent replicates of point process data which may be used for various purposes, e.g. testing sta- tistical hypothesis. The main advantage of this technique is that we do not need to specify any theoretical model for the observed data, only the estimates of se- lected summary characteristics are employed. Main aim of this work is to discuss the possibility of extension of the stochastic reconstruction algorithm for inho- mogeneous point patterns. 1
| Identifer | oai:union.ndltd.org:nusl.cz/oai:invenio.nusl.cz:382736 |
| Date | January 2018 |
| Creators | Koňasová, Kateřina |
| Contributors | Dvořák, Jiří, Prokešová, Michaela |
| Source Sets | Czech ETDs |
| Language | English |
| Detected Language | English |
| Type | info:eu-repo/semantics/masterThesis |
| Rights | info:eu-repo/semantics/restrictedAccess |
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