Modeling Globular Cluster Counts with Bayesian Latent Models

Rafael S. de Souza; Ana L. Chies-Santos

doi:10.3847/2515-5172/ae1973

Modeling Globular Cluster Counts with Bayesian Latent Models

Rafael S. de Souza
, Ana L. Chies-Santos

Research output: Contribution to journal › Article › peer-review

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Abstract

We present a Bayesian latent model to describe the scaling relation between globular cluster populations and their host galaxies, updating the framework proposed in R. S. de Souza et al. Globular cluster counts are drawn from a negative-binomial (NB) process linked to host stellar mass, augmented with a newly introduced Gaussian observation layer that enables efficient propagation of measurement errors. The revised formulation preserves the underlying NB process while improving computational tractability. The code snippets, implemented in Nimble and PyMC are released under the MIT license at this repository ✎.

Original language	English
Number of pages	3
Journal	Research Notes of the American Astronomical Society
Volume	9
Issue number	11
DOIs	https://doi.org/10.3847/2515-5172/ae1973
Publication status	Published - 3 Nov 2025

Keywords

Astrostatistics techniques
Globular star clusters

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10.3847/2515-5172/ae1973Licence: CC BY

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© 2025 The Author(s). This is an open access article distributed under the Creative Commons Attribution License, to view a copy of the license, see: https://creativecommons.org/licenses/by/4.0/.
Final published version, 389 KBLicence: CC BY

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AU - Chies-Santos, Ana L.

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AB - We present a Bayesian latent model to describe the scaling relation between globular cluster populations and their host galaxies, updating the framework proposed in R. S. de Souza et al. Globular cluster counts are drawn from a negative-binomial (NB) process linked to host stellar mass, augmented with a newly introduced Gaussian observation layer that enables efficient propagation of measurement errors. The revised formulation preserves the underlying NB process while improving computational tractability. The code snippets, implemented in Nimble and PyMC are released under the MIT license at this repository ✎.

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JO - Research Notes of the American Astronomical Society

JF - Research Notes of the American Astronomical Society

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Modeling Globular Cluster Counts with Bayesian Latent Models

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Keywords

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