On the Bayesian estimation for the stationary Neyman-Scott point processes.
type: Item
instance of: scholarly article
title: On the Bayesian estimation for the stationary Neyman-Scott point processes.
zbMATH Open document ID: 1413.62134
author: Jiří Kopecký
author: T. Mrkvicka
published in: Applications of Mathematics
publication date: 2016-10-26T00:00:00Z
full work available at URL: http://hdl.handle.net/10338.dmlcz/145798
Mathematics Subject Classification ID: 62M05
Mathematics Subject Classification ID: 62H12
Mathematics Subject Classification ID: 60G55
zbMATH DE Number: 6644009
zbMATH Keywords: Bayesian method
zbMATH Keywords: Monte Carlo Markov chain
zbMATH Keywords: Neyman-Scott point process
zbMATH Keywords: parameter estimation
zbMATH Keywords: shot-noise Cox process
zbMATH Keywords: Thomas process
describes a project that uses: spatstat
describes a project that uses: Mathematica
MaRDI profile type: Publication
OpenAlex ID: W2480919458
cites work: Q5186563
cites work: Q4915366
cites work: A Composite Likelihood Approach in Fitting Spatial Point Process Models
cites work: Statistical Analysis and Modelling of Spatial Point Patterns
cites work: Q3608237
cites work: Distinguishing different types of inhomogeneity in Neyman-Scott point processes
cites work: Two step estimation for Neyman-Scott point process with inhomogeneous cluster centers
cites work: Q4842952
DOI: 10.1007/S10492-016-0144-8
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description: scientific article; zbMATH DE number 6644009