sppmix: Poisson point process modeling using normal mixture models

DOI10.1007/s00180-018-0805-zzbMath1417.62009OpenAlexW2791824221MaRDI QIDQ1729311

Athanasios C. Micheas, Jiaxun Chen

Publication date: 27 February 2019

Published in: Computational Statistics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/s00180-018-0805-z

zbMATH Keywords

Poisson point processhierarchical Bayesian modelsbirth-death MCMCdata-augmentation MCMCmarked point process via conditioning

Mathematics Subject Classification ID

Inference from spatial processes (62M30) Software, source code, etc. for problems pertaining to statistics (62-04) Bayesian inference (62F15) Numerical analysis or methods applied to Markov chains (65C40) Point processes (e.g., Poisson, Cox, Hawkes processes) (60G55)

Related Items (2)

Cox Point Processes: Why One Realisation Is Not Enough ⋮ sppmix

Uses Software

• R
• spatstat
• ggplot2
• R-Geo
• INLA
• fields
• Rcpp
• RcppArmadillo
• lgcp

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