Keeley, Ryan E.Shafieloo, ArmanL'Huillier, BenjaminLinder, Eric V.2019-07-192019-07-192019-05-27Eric V.Linder et al. (2019). Debiasing Cosmic Gravitational Wave Sirens. The 2nd international conference of the Energetic Cosmos Laboratory (ECL) at Nazarbayev University. Retrieved from https://arxiv.org/pdf/1905.10216.pdfhttp://nur.nu.edu.kz/handle/123456789/4015Energetic Cosmos Laboratory. ECL Publication, 2019Accurate estimation of the Hubble constant, and other cosmological parameters, from distances measured by cosmic gravitational wave sirens requires sufficient allowance for the dark energy evolution. We demonstrate how model independent statistical methods, specifically Gaussian process regression, can remove bias in the reconstruction of H(z), and can be combined model independently with supernova distances.enAttribution-NonCommercial-ShareAlike 3.0 United StatesThe 2nd international conference of the Energetic Cosmos Laboratory (ECL)Energetic Cosmos Laboratory (ECL)ECL19Article