Statistics for the stationary strauss model by the cusp point method

DOI10.1080/02331889108802310zbMath0809.62078OpenAlexW2013946301MaRDI QIDQ4322953

Dietrich Stoyan, P. Grabarnik

Publication date: 26 March 1995

Published in: Unnamed Author (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/02331889108802310

zbMATH Keywords

second-order characteristicsMonte Carlo experimentsGibbs processcusp point methodstationary hard-core Strauss model

Mathematics Subject Classification ID

Inference from spatial processes (62M30) Non-Markovian processes: estimation (62M09) Point processes (e.g., Poisson, Cox, Hawkes processes) (60G55)

Related Items (1)

Marked Point Process: Using Correlation Functions to Explore a Spatial Data Set

Uses Software

• spatial

Cites Work

• Mean characteristics of Gibbsian point processes
• Poisson limits for a hard-core clustering model
• Unnamed Item

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