Kernel Selection for Gaussian Process in Cosmology: With Approximate Bayesian Computation Rejection and Nested Sampling

Kernel Selection for Gaussian Process in Cosmology: With Approximate Bayesian Computation Rejection and Nested Sampling

The Gaussian process (GP) has gained much attention in cosmology due to its ability to reconstruct cosmological data in a model-independent manner. In this study, we compare two methods for GP kernel selection: approximate Bayesian computation (ABC) rejection and nested sampling. We analyze three ty...

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Bibliographic Details
Main Authors: Hao Zhang, Yu-Chen Wang, Tong-Jie Zhang, Tingting Zhang
Format: Article
Language:English
Published: IOP Publishing 2023-01-01
Series:The Astrophysical Journal Supplement Series
Subjects:
Gaussian Processes regression
Astronomy data analysis
Bayes factor
Observational cosmology
Astrostatistics strategies
Online Access:https://doi.org/10.3847/1538-4365/accb92

Internet

https://doi.org/10.3847/1538-4365/accb92

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