On parameter estimation for doubly inhomogeneous cluster point processes
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F60076658%3A12510%2F17%3A43892131" target="_blank" >RIV/60076658:12510/17:43892131 - isvavai.cz</a>
Result on the web
<a href="http://dx.doi.org/10.1016/j.spasta.2017.03.005" target="_blank" >http://dx.doi.org/10.1016/j.spasta.2017.03.005</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1016/j.spasta.2017.03.005" target="_blank" >10.1016/j.spasta.2017.03.005</a>
Alternative languages
Result language
angličtina
Original language name
On parameter estimation for doubly inhomogeneous cluster point processes
Original language description
Nowadays, spatial inhomogeneity and clustering are two important features frequently observed in point patterns. These features often reveal heterogeneity of processes/factors involved in the point pattern formation and interaction determining the relative locations of points. Thus, inhomogeneous cluster point processes can be viewed as flexible and relevant models for describing point patterns observed in biology, forestry and economics for example. In this article, we consider cluster point processes with double inhomogeneity in which locations of cluster centers are drawn under an inhomogeneous parametric intensity function and the distribution of clusters is spatially inhomogeneous and depends on a given parametric function. We propose a Bayesian estimation procedure based on an MCMC algorithm to simultaneously estimate inhomogeneity parameters, cluster parameters and cluster centers. This modeling and estimation framework was applied to a toy case study dealing with the small-scale dispersal of spores of a fungal pathogen infecting plants.
Czech name
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Czech description
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Classification
Type
J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database
CEP classification
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OECD FORD branch
10103 - Statistics and probability
Result continuities
Project
<a href="/en/project/GA16-03708S" target="_blank" >GA16-03708S: Spatial geometrical statistics of random sets in Euclidean spaces</a><br>
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)
Others
Publication year
2017
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Name of the periodical
Spatial Statistics
ISSN
2211-6753
e-ISSN
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Volume of the periodical
2017
Issue of the periodical within the volume
20
Country of publishing house
GB - UNITED KINGDOM
Number of pages
15
Pages from-to
191-205
UT code for WoS article
000405608800009
EID of the result in the Scopus database
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