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Activity Number: 415 - Astrostatistics: Innovative Statistical Methods for Foundational Astrophysical Sciences
Type: Topic Contributed
Date/Time: Wednesday, August 10, 2022 : 10:30 AM to 12:20 PM
Sponsor: Korean International Statistical Society
Abstract #320948
Title: Model Validation and Estimation of Mass-Radius-Flux Distribution for Exoplanets Under Heterogeneous Measurement Errors
Author(s): Sujit Ghosh* and Qi Ma
Companies: North Carolina State University and Facebook Inc
Keywords: astronomy; bayesian; model validation; mc methods

Bayesian hierarchical models (BHM) are being routinely used for astronomy data. However, with the recent advent of computing power, although a lot of complex statistical models can be fitted using Monte Carlo methods, it has largely remained illusive how to validate these complex models when the data are observed with heterogeneous large measurement errors. We illustrate the methodology using a non-trivial extension of the M–R relation by including the incident flux as an additional variable. By using BHM that leverages the flexibility of finite mixture models, a probabilistic mass–radius–flux relationship (M–R–F relation) is obtained based on a sample of 319 exoplanets. We find that the flux has non-negligible impact on the M–R relation, while such impact is strongest for hot Jupiters. On the population level, the planets with higher level of flux tend to be denser, and high flux could trigger significant mass loss for plants with larger radii. We present two novel methods to examine model assumptions, which can be used not only for the M-R-F models but can also be adapted for other statistical models.

Authors who are presenting talks have a * after their name.

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