Published January 8, 2020 | Version v1
Poster Open

PolyChord: next generation nested sampling

Authors/Creators

  • 1. Kavli Institute for Cosmology, Cambridge University

Description

Paper references:

  1. John Skilling. Nested sampling for general bayesian computation. Bayesian analysis, 1(4):833–859, 2006.
  2. D. Sivia and J. Skilling. Data Analysis: A Bayesian Tutorial. Oxford science publications. OUP Oxford, 2006.
  3. Feroz, Hobson, and Bridges. MULTINEST: an efficient and robust Bayesian inference tool for cosmology and particle physics. MNRAS, 398(4):1601–1614, Oct 2009.
  4. F. Feroz and J. Skilling. Exploring multi-modal distributions with nested sampling. In American IoP Conference Series, volume 1553, pages 106–113, Aug 2013.
  5. Michael Betancourt. Nested Sampling with Constrained Hamiltonian Monte Carlo. In American IofP Conference Series, volume 1305, pages 165–172, Mar 2011.
  6. Adam Moss. Accelerated Bayesian inference using deep learning. arXiv e-prints, page arXiv:1903.10860, Mar 2019.
  7. Joshua S Speagle. dynesty: A Dynamic Nested Sampling Package for Estimating Bayesian Posteriors and Evidences. arXiv e-prints, page arXiv:1904.02180, Apr 2019.
  8. W. J. Handley, A. N. Lasenby, H. V. Peiris, and M. P. Hobson. Bayesian inflationary reconstructions from Planck 2018 data. PRD, 100(10):103511, Nov 2019.
  9. Will Handley. Curvature tension: evidence for a closed universe. arXiv, 1908.09139, Aug 2019.
  10. Hall, Thompson, Handley, and Queloz. On the Feasibility of Intense Radial Velocity Surveys for Earth-Twin Discoveries. MNRAS, 479(3):2968–2987, Sep 2018.
  11. Gregory D. Martinez, James McKay, Ben Farmer, Pat Scott, Elinore Roebber, Antje Putze, and Jan Conrad. Comparison of statistical sampling methods with ScannerBit, the GAMBIT scanning module. European Physical Journal C, 77(11):761, Nov 2017.
  12.  Xi Chen, Farhan Feroz, and Michael Hobson. Bayesian automated posterior repartitioning for nested sampling. arXiv e-prints, page arXiv:1908.04655, Aug 2019.
  13. W. Handley and J. Alsing. Compromise-free Likelihood free inference. Bayesian analysis (In preparation), 2020.
  14. Will Handley. anesthetic: nested sampling visualisation. JOSS, 4:1414, May 2019.
  15. E. Higson, W. Handley, L Hobson, and A Lasenby. Dynamic nested sampling. Statistics and Computation, 29(5):891–913, Sep 2019.
  16. Brendon J. Brewer and Daniel Foreman-Mackey. DNest4: Diffusive Nested Sampling in C++ and Python. arXiv e-prints, page arXiv:1606.03757, Jun 2016.
  17. Stefano Martiniani, Jacob D Stevenson, David J Wales, and Daan Frenkel. Superposition enhanced nested sampling. Physical Review X, 4(3):031034, 2014.
  18. Philip Graff, Farhan Feroz, Michael P. Hobson, and Anthony Lasenby. BAMBI: blind accelerated multimodal Bayesian inference. MNRAS, 421(1):169–180, Mar 2012.
  19. W. J. Handley, M. P. Hobson, and A. N. Lasenby. polychord: nested sampling for cosmology. MNRAS, 450:L61–L65, Jun 2015.
  20. W. J. Handley, M. P. Hobson, and A. N. Lasenby. POLYCHORD: next-generation nested sampling. MNRAS, 453(4):4384–4398, Nov 2015.
  21. K. Javid, W. J. Handley, M. P. Hobson, and L. Lasenby. Compromise-free Bayesian neural networks. Bayesian analysis (In preparation), 2020.

Notes

Presented at Mathematical Challenges in the Electromagnetic Environment Workshop, 8-10 January 2020, Cambridge https://gateway.newton.ac.uk/event/tgmw74

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