12.4k citations · 12.6k across the 9 of their papers we have counts for
3 papers · 1 filter
The Probabilities of Orbital-Companion Models for Stellar Radial Velocity Data
Fengji Hou, Jonathan Goodman, David W. Hogg
The fully marginalized likelihood, or Bayesian evidence, is of great importance in probabilistic data analysis, because it is involved in calculating the posterior probability of a…
emcee: The MCMC Hammer
Daniel Foreman-Mackey, David W. Hogg, Dustin Lang +1
We introduce a stable, well tested Python implementation of the affine-invariant ensemble sampler for Markov chain Monte Carlo (MCMC) proposed by Goodman & Weare (2010). The code i…
An Affine-Invariant Sampler for Exoplanet Fitting and Discovery in Radial Velocity Data
Fengji Hou, Jonathan Goodman, David W. Hogg +2
Markov Chain Monte Carlo (MCMC) proves to be powerful for Bayesian inference and in particular for exoplanet radial velocity fitting because MCMC provides more statistical informat…