Inference for the dark energy equation of state using type IA supernova data

DOI10.1214/08-AOAS229zbMath1161.62086arXiv0805.4136MaRDI QIDQ1018610

Robert C. Nichol, Christopher R. Genovese, Larry Alan Wasserman, Peter E. Freeman, Christopher J. Miller

Publication date: 20 May 2009

Published in: The Annals of Applied Statistics (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/0805.4136

zbMATH Keywords

nonlinear inverse problemsnonparametric inferencedark energy

Mathematics Subject Classification ID

Applications of statistics to physics (62P35) Astrophysical cosmology (85A40) Statistical astronomy (85A35)

Related Items

Sequentially guided MCMC proposals for synthetic likelihoods and correlated synthetic likelihoods, Inference for the dark energy equation of state using type IA supernova data

Cites Work

• Unnamed Item
• Unnamed Item
• Unnamed Item
• Nonparametric regression, confidence regions and regularization
• Inference for the dark energy equation of state using type IA supernova data
• Estimating the dimension of a model
• Bootstrap methods: another look at the jackknife
• Cardassian expansion: a model in which the universe is flat, matter dominated, and accelerating
• Honest confidence regions for nonparametric regression
• Nonparametric goodness-of-fit testing under Gaussian models
• Confidence balls in Gaussian regression.
• CLASSICALITY OF PRIMORDIAL FLUCTUATIONS AND PRIMORDIAL BLACK HOLES
• Cosmological Physics
• Measurements of Ω and Λ from 42 High‐Redshift Supernovae
• Inflationary universe: A possible solution to the horizon and flatness problems
• The cosmological constant problem
• A practical guide to splines.