Time delay likelihoods modeled with Gaussian processes develop a boundary-driven W-shape with a global maximum at the true delay and rises at observation window edges, misleading nested sampling and biasing H0 high.
Skilling, Nested sampling for general Bayesian compu- tation, Bayesian Analysis1, 833 (2006)
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Basilic is an end-to-end Bayesian pipeline for gravitational-wave burst inference and model classification, with a case study showing signal degeneracies between binary black hole mergers and cosmic strings.
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Global structure of the time delay likelihood
Time delay likelihoods modeled with Gaussian processes develop a boundary-driven W-shape with a global maximum at the true delay and rises at observation window edges, misleading nested sampling and biasing H0 high.
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Basilic: An end-to-end pipeline for Bayesian burst inference and model classification in gravitational-wave data
Basilic is an end-to-end Bayesian pipeline for gravitational-wave burst inference and model classification, with a case study showing signal degeneracies between binary black hole mergers and cosmic strings.