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We have developed a frequentist approach for model selection which determines the consistency between any cosmological model and the data using the distribution of likelihoods from the iterative smoothing method.
1903
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A.G. Riess, A.V. Filippenko, P. Challis, A. Clocchiatti, A. Diercks, P.M. Garnavich et al., Observational Evidence from Supernovae for an Accelerating Universe and a Cosmological Constant , AJ 116
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A. Shafieloo, U. Alam, V. Sahni and A.A. Starobinsky, Smoothing supernova data to reconstruct the expansion history of the Universe and its age , MNRAS 366
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A.G. Riess, L.-G. Strolger, S. Casertano, H.C. Ferguson, B. Mobasher, B. Gold et al., New Hubble Space Telescope Discoveries of Type Ia Supernovae at z >= 1: Narrowing Constraints on the Early Behavior of Dark Energy , ApJ 659
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R.E. Keeley, A. Shafieloo, G.-B. Zhao, J.A. Vazquez and H. Koo, Reconstructing the Universe: Testing the Mutual Consistency of the Pantheon and SDSS/eBOSS BAO Data Sets with Gaussian Processes , AJ 161
2021
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