Fast and reliable Markov chain Monte Carlo technique for cosmological parameter estimation

By J. Dunkley, M. Bucher, Pedro G. Ferreira, K. Moodley, C. Skordis. 2005

181 citations recorded by the source corpus.

Subfields: Astronomy and Astrophysics, Statistical and Nonlinear Physics

View Paper: https://www.semanticscholar.org/paper/2a04fc8da00da5cce9da44492b1b3acd6c54a9ef

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In Astronomy and Astrophysics

In Statistical and Nonlinear Physics

Citations in the corpus

Using the Full Power of the Cosmic Microwave Background to Probe Axion Dark Matter (2017, methodology): “We assess convergence of our chains using the spectral method of Dunkley et al. (2005).”
THE FLAT TRANSMISSION SPECTRUM OF THE SUPER-EARTH GJ1214b FROM WIDE FIELD CAMERA 3 ON THE HUBBLE SPACE TELESCOPE (2011, methodology): “When generating each new trial parameter set M′j+1, we follow Dunkley et al. (2005) and perturb every parameter at once, drawing the parameter jumps from a multivariate Gaussian with a covariance matrix that approximates that of the parameter distribution.”
THE STELLAR INITIAL MASS FUNCTION IN EARLY-TYPE GALAXIES FROM ABSORPTION LINE SPECTROSCOPY. II. RESULTS (2012, background): “Convergence is defined according to the prescription described in Dunkley et al. (2005).”
Dimensionality reduction and polynomial chaos acceleration of Bayesian inference in inverse problems (2008, methodology): “It may be possible to design more efficient MCMC methods for both cases, perhaps updating blocks of components at a time with suitably shaped proposals, but reducing the chain dimension will inevitably enable greater efficiency [73] and reduce the number of posterior evaluations required.”
emcee: The MCMC Hammer (2012, methodology): “In astrophysics, spectral methods have been used extensively (for example Dunkley et al. 2005).”
COSMOLOGICAL CONSTRAINTS FROM THE SLOAN DIGITAL SKY SURVEY MaxBCG CLUSTER CATALOG (2009, methodology): “The likelihood function is sampled using a Monte Carlo Markov Chain (MCMC) approach with a burn in of 22,000 points during which the covariance matrix of the parameters is continually updated so as to provide an ideal sampling rate (Dunkley et al. 2005).”
Modeling the evolution of infrared galaxies: a parametric backward evolution model (2010, methodology): “We used a Monte Carlo Markov chain (MCMC) MetropolisHastings algorithm (Chib & Greenberg 1995; Dunkley et al. 2005) to fit our model.”
THE ATACAMA COSMOLOGY TELESCOPE: COSMOLOGICAL PARAMETERS FROM THE 2008 POWER SPECTRUM (2010, methodology): “We use the MCMC code and methodology described in Appendix C of Dunkley et al. (2009), with the convergence test described in Dunkley et al. (2005).”
TWO ACCURATE TIME-DELAY DISTANCES FROM STRONG LENSING: IMPLICATIONS FOR COSMOLOGY (2012, methodology): “…modeled time-delay distance, all mass parameters of G, the Einstein radius of S, external shear, the extended source intensity distribution, and the lens light profile of G. Glee employs several of the methods of Dunkley et al. (2005) for efficient MCMC sampling and for assessing chain convergence.”
THE AVERAGE STAR FORMATION HISTORIES OF GALAXIES IN DARK MATTER HALOS FROM z = 0–8 (2012, background): “Although the algorithm of Dunkley et al. (2005) indicates that we converge after only 5×105 points, we continue to run for 4×106 total points to minimize the chance of unexplored regions and to ensure that the adaptive updates of the step covariance matrix converge and do not bias our final results.”
A COMPREHENSIVE ANALYSIS OF UNCERTAINTIES AFFECTING THE STELLAR MASS–HALO MASS RELATION FOR 0 < z < 4 (2010, methodology): “We verify convergence according to the algorithm in Dunkley et al. (2005); in all cases, the ratio of the sample mean variance to the distribution variance (the “convergence ratio”) is below 0.005.”
The ATLAS3D project XV: benchmark for early-type galaxies scaling relations from 260 dynamical models: mass-to-light ratio, dark matter, fundamental plane and mass plane (2012, methodology): “This natural idea is similar to what is routinely done e.g. in the determination of cosmological parameters, where the covariance matrix of the posterior is calculated after a burn-in phase (e.g. Dunkley et al. 2005).”
New Hubble Space Telescope Discoveries of Type Ia Supernovae at z ≥ 1: Narrowing Constraints on the Early Behavior of Dark Energy (2006, background): “A set of parameters that is accepted to the chain forms a new starting point for the next guess, and the process is repeated for a sufficient number of steps (convergence can be checked via the method of Dunkley et al. 2005).”