docs/paper/paper.bib
@article{Skilling2006,
author = {Skilling, John},
doi = {10.1214/06-BA127},
issn = {19360975},
journal = {Bayesian Analysis},
keywords = {Algorithm,Annealing,Bayesian computation,Evidence,Marginal likelihood,Model selection,Nest,Phase change},
number = {4},
pages = {833--860},
title = {{Nested sampling for general Bayesian computation}},
volume = {1},
year = {2006}
}
@article{Feroz2013,
archivePrefix = {arXiv},
arxivId = {1306.2144},
author = {Feroz, F. and Hobson, M. P. and Cameron, E. and Pettitt, A. N.},
eprint = {1306.2144},
journal = {arXiv preprint arXiv:1306.2144},
keywords = {bayesian methods,data analysis,model selection,monte carlo methods},
title = {{Importance Nested Sampling and the MultiNest Algorithm}},
url = {https://arxiv.org/abs/1306.2144},
year = {2013}
}
@article{Feroz2009,
archivePrefix = {arXiv},
arxivId = {0809.3437},
author = {Feroz, F. and Hobson, M. P. and Bridges, M.},
doi = {10.1111/j.1365-2966.2009.14548.x},
eprint = {0809.3437},
isbn = {0035-8711},
issn = {00358711},
journal = {Monthly Notices of the Royal Astronomical Society},
keywords = {Methods: Data analysis,Methods: Statistical},
month = {sep},
number = {4},
pages = {1601--1614},
title = {{MultiNest: an efficient and robust Bayesian inference tool for cosmology and particle physics}},
url = {http://dx.doi.org/10.1111/j.1365-2966.2009.14548.x},
volume = {398},
year = {2008}
}
@article{Feroz2008,
archivePrefix = {arXiv},
arxivId = {arXiv:0704.3704v3},
author = {Feroz, F. and Hobson, M. P.},
doi = {10.1111/j.1365-2966.2007.12353.x},
eprint = {arXiv:0704.3704v3},
isbn = {0035-8711},
issn = {00358711},
journal = {Monthly Notices of the Royal Astronomical Society},
keywords = {Methods: data analysis,Methods: statistical},
number = {2},
pages = {449--463},
pmid = {358711},
title = {{Multimodal nested sampling: An efficient and robust alternative to Markov Chain Monte Carlo methods for astronomical data analyses}},
volume = {384},
year = {2008}
}
@article{Handley2015b,
archivePrefix = {arXiv},
arxivId = {1506.00171},
author = {Handley, W. J. and Hobson, M. P. and Lasenby, A. N.},
doi = {10.1093/mnras/stv1911},
eprint = {1506.00171},
journal = {Monthly Notices of the Royal Astronomical Society},
keywords = {data analysis,methods,statistical},
pages = {1--15},
title = {{PolyChord: next-generation nested sampling}},
volume = {15},
year = {2015}
}
@article{Handley2015a,
archivePrefix = {arXiv},
arxivId = {1502.01856},
author = {Handley, W. J. and Hobson, M. P. and Lasenby, A. N.},
doi = {10.1093/mnrasl/slv047},
eprint = {1502.01856},
issn = {17453933},
journal = {Monthly Notices of the Royal Astronomical Society: Letters},
keywords = {Methods: data analysis,Methods: statistical},
number = {1},
pages = {L61--L65},
title = {{PolyChord: Nested sampling for cosmology}},
volume = {450},
year = {2015}
}
@article{Higson2017a,
abstract = {Sampling errors in nested sampling parameter estimation differ from those in Bayesian evidence calculation, but have been little studied in the literature. This paper provides the first explanation of the two main sources of sampling errors in nested sampling parameter estimation, and presents a new diagrammatic representation for the process. We find no current method can accurately measure the parameter estimation errors of a single nested sampling run, and propose a method for doing so using a new algorithm for dividing nested sampling runs. We empirically verify our conclusions and the accuracy of our new method.},
archivePrefix = {arXiv},
arxivId = {1703.09701},
author = {Higson, Edward and Handley, Will and Hobson, Mike and Lasenby, Anthony},
doi = {doi:10.1214/17-BA1075},
eprint = {1703.09701},
journal = {Bayesian Analysis},
keywords = {nested sampling,parameter estimation},
number = {3},
pages = {873--896},
title = {{Sampling errors in nested sampling parameter estimation}},
url = {https://doi.org/10.1214/17-BA1075},
volume = {13},
year = {2018}
}
@article{Higson2017b,
archivePrefix = {arXiv},
arxivId = {1704.03459},
author = {Higson, Edward and Handley, Will and Hobson, Mike and Lasenby, Anthony},
eprint = {1704.03459},
journal = {arXiv preprint arXiv:1704.03459},
keywords = {bayesian evidence,nested sampling,parameter estimation},
title = {{Dynamic nested sampling: an improved algorithm for parameter estimation and evidence calculation}},
url = {https://arxiv.org/abs/1704.03459},
year = {2017}
}
@article{Higson2018a,
archivePrefix = {arXiv},
arxivId = {1804.06406},
author = {Higson, Edward and Handley, Will and Hobson, Mike and Lasenby, Anthony},
eprint = {1804.06406},
journal = {arXiv preprint arXiv:1804.06406},
title = {{nestcheck: diagnostic tests for nested sampling calculations}},
url = {https://arxiv.org/abs/1804.06406},
year = {2018}
}
@article{Higson2018b,
author = {Higson, Edward and Handley, William and Lasenby, Anthony and Hobson, Mike},
journal = {arXiv preprint arXiv:1809.04598},
title = {{Bayesian sparse reconstruction: a brute-force approach to astronomical imaging and machine learning}},
url = {https://arxiv.org/abs/1809.04598},
year = {2018}
}
@article{Higson2018nestcheck,
author = {Higson, Edward},
doi = {10.21105/joss.00916},
journal = {Journal of Open Source Software},
number = {29},
pages = {916},
title = {{nestcheck: error analysis, diagnostic tests and plots for nested sampling calculations}},
volume = {3},
year = {2018}
}
@article{Chua2018,
archivePrefix = {arXiv},
arxivId = {1803.10210},
author = {Chua, Alvin J. K. and Hee, Sonke and Handley, Will J. and Higson, Edward and Moore, Christopher J. and Gair, Jonathan R. and Hobson, Michael P. and Lasenby, Anthony N.},
doi = {10.1093/mnras/sty1079},
eprint = {1803.10210},
journal = {Monthly Notices of the Royal Astronomical Society},
keywords = {data analysis,gravitational waves,methods,statistical},
number = {1},
pages = {28--40},
title = {{Towards a framework for testing general relativity with extreme-mass-ratio-inspiral observations}},
url = {http://dx.doi.org/10.1093/mnras/sty1079},
volume = {478},
year = {2018}
}
@article{DESCollaboration2017,
archivePrefix = {arXiv},
arxivId = {1708.01530},
author = {{DES Collaboration}},
doi = {10.1103/PhysRevD.98.043526},
eprint = {1708.01530},
journal = {Phys. Rev. D},
number = {4},
title = {{Dark Energy Survey Year 1 Results: Cosmological Constraints from Galaxy Clustering and Weak Lensing}},
volume = {98},
year = {2018}
}
@misc{zenododypolychord,
author = {Higson, Edward},
doi = {10.5281/zenodo.1328175},
title = {{dyPolyChord: dynamic nested sampling with PolyChord}},
year = {2018}
}
@article{Higson2018perfectns,
author = {Higson, Edward},
doi = {10.5281/zenodo.1327591},
title = {{perfectns: perfect dynamic and standard nested sampling for spherically symmetric likelihoods and priors}},
year = {2018}
}
@article{Dalcin2011,
author = {Dalcin, Lisandro D. and Paz, Rodrigo R. and Kler, Pablo A. and Cosimo, Alejandro},
doi = {10.1016/j.advwatres.2011.04.013},
isbn = {0309-1708},
issn = {03091708},
journal = {Advances in Water Resources},
number = {9},
pages = {1124--1139},
publisher = {Elsevier Ltd},
title = {{Parallel distributed computing using Python}},
url = {http://dx.doi.org/10.1016/j.advwatres.2011.04.013},
volume = {34},
year = {2011}
}
@misc{Jones2001,
author = {Jones, Eric and Oliphant, Travis and Peterson, Pearu and Others},
title = {SciPy: Open source scientific tools for Python},
url = {http://www.scipy.org/},
year = {2001}
}
@book{Oliphant2006,
title={A guide to NumPy},
author={Oliphant, Travis E},
volume={1},
year={2006},
publisher={Trelgol Publishing USA}
}