Ensemble samplers with affine invariance

By Jonathan R Goodman, Jonathan Weare. 2010

2,466 citations recorded by the source corpus.

Subfields: Artificial Intelligence, Condensed Matter Physics, Statistics and Probability

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Citations in the corpus

STELLAR AND PLANETARY PROPERTIES OF K2 CAMPAIGN 1 CANDIDATES AND VALIDATION OF 17 PLANETS, INCLUDING A PLANET RECEIVING EARTH-LIKE INSOLATION (2015, background): “…of the affine-invariant 11 http://www.astro.princeton.edu/~tdm/k2/ 12 http://phoenix.ens-lyon.fr/Grids/BT-Settl/CIFIST2011/ ensemble sampler of Goodman & Weare (2010) to sample from the posterior probability distribution for the stellar—limb darkening coefficients, mass, radius, and effective…”
Stan: A Probabilistic Programming Language (2017, methodology): “Two ﬂavors of ensemble samplers are also in the works: an aﬃne invariant ensemble sampler (Goodman and Weare 2010) and a diﬀerential evolution sampler (Ter Braak 2006).”
Multiwavelength analysis for interferometric (sub-)mm observations of protoplanetary disks - Radial constraints on the dust properties and the disk structure (2015, methodology): “We adopt an affine-invariant ensemble sampler for MCMC proposed by Goodman & Weare (2010), which is designed to simultaneously run several Markov chains (also called walkers) interacting with each other to converge to the maximum of the posterior.”
Neutron star mass and radius measurements from atmospheric model fits to X-ray burst cooling tail spectra (2017, methodology): “To explore the parameter spaces we implement an affine-invariant ensemble sampler as discussed in Goodman & Weare 2010 (see also Guillot et al. 2013).”
The Exoplanet Population Observation Simulator. I. The Inner Edges of Planetary Systems (2018, methodology): “We use emcee(Foreman-Mackey et al. 2013), an open-source Pythonimplementation of the algorithm by Goodman & Weare (2010) to sample the parameter space and estimate the posterior distribution of parameters.”
New Spectral Model for Constraining Torus Covering Factors from Broadband X-Ray Spectra of Active Galactic Nuclei (2018, methodology): “We quote uncertainties on the fitted model parameters based on marginalized probability distributions derived from converged MCMC chains produced with the built-in Goodman & Weare (2010) MCMC algorithm in Xspec.”
CHARACTERIZING K2 PLANET DISCOVERIES: A SUPER-EARTH TRANSITING THE BRIGHT K DWARF HIP 116454 (2014, methodology): “We rederived the SFF correction by fitting the K2 light curve using an MCMC algorithm with an affine invariant ensemble sampler (adapted for IDL from the algorithm of Goodman & Weare 2010; Foreman-Mackey et al. 2013).”
UniverseMachine: The correlation between galaxy growth and dark matter halo assembly from z = 0−10 (2018, methodology): “The likelihood function (exp(−χ2/2)) is processed through an MCMC algorithm (a hybrid of adaptive Metropolis and stretch-step MCMC algorithms; Haario et al. 2001; Goodman & Weare 2010), resulting in empirical constraints on how galaxy growth correlates with halo growth.”
A Three-dimensional View of Turbulence: Constraints on Turbulent Motions in the HD 163296 Protoplanetary Disk Using DCO+ (2017, methodology): “To derive the posterior distributions for each parameter, we employ the MCMC routine EMCEE (Foreman-Mackey et al. 2013) based on the affine-invariant algorithm originally proposed in Goodman & Weare (2010).”
The Disk Substructures at High Angular Resolution Project (DSHARP). II. Characteristics of Annular Substructures (2018, positive): “The posteriors are explored with the affine invariant MCMC sampler implemented in emcee (Goodman & Weare 2010; Foreman-Mackey et al. 2013).”
EMERGE – an empirical model for the formation of galaxies since z ∼ 10 (2017, methodology): “We sample the posterior using the affine invariant ensemble sampler for MCMC presented by Goodman & Weare (2010).”
How to Constrain Your M Dwarf. II. The Mass–Luminosity–Metallicity Relation from 0.075 to 0.70 Solar Masses (2018, methodology): “We used the Monte Carlo Markov Chain (MCMC) software emcee (ForemanMackey et al. 2013), a Python implementation of the affine-invariant ensemble sampler (Goodman & Weare 2010).”
A Multi-telescope Campaign on FRB 121102: Implications for the FRB Population (2017, methodology): “We used the Goodman and Weare affine invariant sampler (Goodman & Weare 2010) as implemented in emcee (Foreman-Mackey et al. 2013).”