GetDist implements boundary-corrected KDE with automatic smoothing for analyzing weighted and correlated Monte Carlo samples, plus plotting and diagnostic tools.
This KDE accounts for boundary effects from any active priors and is normalized so its peak value is one
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
fields
astro-ph.IM 1years
2019 1verdicts
ACCEPT 1representative citing papers
citing papers explorer
-
GetDist: a Python package for analysing Monte Carlo samples
GetDist implements boundary-corrected KDE with automatic smoothing for analyzing weighted and correlated Monte Carlo samples, plus plotting and diagnostic tools.