Study the galaxy distribution characterisation via Bayesian statistical learning of spatial marked point processes - Archive ouverte HAL
Communication Dans Un Congrès Année : 2023

Study the galaxy distribution characterisation via Bayesian statistical learning of spatial marked point processes

Résumé

Marked point process and Bayesian inference are powerful tools for analysing spatial data. Here the work done by Hurtado Gil et al. (2021) is analysed and a new in-homogeneous with superposed interaction is proposed. The results indicate a correct fit of the model and allow the study of the significance of the parameter at the corresponding prefixed interaction ranges. To this work in progress, immediate conclusions and perspectives are outlined.
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Dates et versions

hal-04163649 , version 1 (17-07-2023)
hal-04163649 , version 2 (23-08-2023)

Identifiants

  • HAL Id : hal-04163649 , version 2

Citer

N Gillot, Radu S. Stoica, Didier Gemmerlé. Study the galaxy distribution characterisation via Bayesian statistical learning of spatial marked point processes. RING Meeting, École nationale supérieure de géologie (ENSG) Nancy, Sep 2023, Nancy, France. ⟨hal-04163649v2⟩
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