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3 claims from 1 paper

1. Mathematics › Markov Chains and Monte Carlo Methods

   GetDist: a Python package for analysing Monte Carlo samples

   Lewis · Journal of Cosmology and Astroparticle Physics · 2025

   The paper describes GetDist, a Python package that analyses Monte Carlo samples, using kernel density estimation for 1D and 2D densities, automatic smoothing, plotting tools and convergence diagnostics.

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   1. UncheckedGetDist's default way of estimating smooth densities from samples uses a linear boundary kernel followed by multiplicative bias correction.“GetDist 's baseline method consists of applying a linear boundary kernel, and then using multiplicative bias correction.”
   2. Unchecked“The smoothing bandwidth is selected automatically following Botev et al. [1], based on a mixture of heuristics and optimization results using the expected scaling with an effective number of samples (defined here to account for both MCMC correlations and wei…
   3. UncheckedGetDist's two-dimensional density smoothing uses an elliptical Gaussian kernel, chosen automatically, when the parameters are correlated.“Two-dimensional KDE uses an automatically-determined elliptical Gaussian kernel for correlated distributions.”