nestcheck: diagnostic tests for nested sampling calculations

Edward Higson, Will Handley, Mike Hobson, Anthony Lasenby
4/16/2018
stat.COastro-ph.COastro-ph.IM

Official code: ejhigson/nestcheck (17 stars, MIT, last commit 2023-07-08).

Abstract

Nested sampling is an increasingly popular technique for Bayesian computation, in particular for multimodal, degenerate problems of moderate to high dimensionality. Without appropriate settings, however, nested sampling software may fail to explore such posteriors correctly; for example producing correlated samples or missing important modes. This paper introduces new diagnostic tests to assess the reliability both of parameter estimation and evidence calculations using nested sampling software, and demonstrates them empirically. We present two new diagnostic plots for nested sampling, and give practical advice for nested sampling software users in astronomy and beyond. Our diagnostic tests and diagrams are implemented in nestcheck: a publicly available Python package for analysing nested sampling calculations, which is compatible with output from MultiNest, PolyChord and dyPolyChord.

View on arXivView PDF

Code Implementations(1)

ejhigson/nestcheckOfficial100%
MIT

Error analysis, diagnostic tests and plots for nested sampling calculations.

1710PythonFeb 11, 20183 years agoMIT
bayesian-inferencedynamic-nested-samplingerror-analysisnested-samplingpython+1 more

Similar Papers

Dynamic nested sampling: an improved algorithm for parameter estimation and evidence calculation

84% match1 repo222017

Sampling Errors in Nested Sampling Parameter Estimation

83% match1 repo172017

PolyChord: nested sampling for cosmology

82% match2 repos1012015

PolyChord: next-generation nested sampling

80% match2 repos1012015

Nested Slice Sampling: Vectorized Nested Sampling for GPU-Accelerated Inference

76% match2026

Importance Nested Sampling and the MultiNest Algorithm

76% match1 repo742013

Cite this paper

@article{higson2018nestcheck,
  title  = {nestcheck: diagnostic tests for nested sampling calculations},
  author = {Edward Higson and Will Handley and Mike Hobson and Anthony Lasenby},
  year   = {2018},
  eprint = {1804.06406},
  archivePrefix = {arXiv},
  url    = {https://arxiv.org/abs/1804.06406}
}

Add a badge to your README

Shows whether official code is linked for this paper.

Code of Paper badge
[![Code of Paper](https://codeofpaper.com/badge/1804.06406.svg)](https://codeofpaper.com/paper/1804.06406)

Discussion