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    Rights statement: The Author's Accepted Manuscript (the accepted version of the manuscript as submitted by the author) may only be posted 6 months after the paper is published, consistent with our self-archiving embargo. Please note that the Author’s Accepted Manuscript may not be released under a Creative Commons license. For Nature Research Terms of Reuse of archived manuscripts please see: http://www.nature.com/authors/policies/license.html#terms

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Nested sampling for physical scientists

Research output: Contribution to Journal/Magazine › Journal article › peer-review

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Nested sampling for physical scientists. / Ashton, Greg; Bernstein, Noam; Buchner, Johannes et al.
In: Nature Reviews Methods Primers, Vol. 2, No. 1, 39, 31.12.2022.

Research output: Contribution to Journal/Magazine › Journal article › peer-review

Harvard

Ashton, G, Bernstein, N, Buchner, J, Chen, X, Csányi, G, Fowlie, A, Feroz, F, Griffiths, M, Handley, W, Habeck, M, Higson, E, Hobson, M, Lasenby, A, Parkinson, D, Pártay, LB, Pitkin, M, Schneider, D, Speagle, JS, South, L, Veitch, J, Wacker, P, Wales, DJ & Yallup, D 2022, 'Nested sampling for physical scientists', Nature Reviews Methods Primers, vol. 2, no. 1, 39. https://doi.org/10.1038/s43586-022-00121-x

APA

Ashton, G., Bernstein, N., Buchner, J., Chen, X., Csányi, G., Fowlie, A., Feroz, F., Griffiths, M., Handley, W., Habeck, M., Higson, E., Hobson, M., Lasenby, A., Parkinson, D., Pártay, L. B., Pitkin, M., Schneider, D., Speagle, J. S., South, L., ... Yallup, D. (2022). Nested sampling for physical scientists. Nature Reviews Methods Primers, 2(1), Article 39. Advance online publication. https://doi.org/10.1038/s43586-022-00121-x

Vancouver

Ashton G, Bernstein N, Buchner J, Chen X, Csányi G, Fowlie A et al. Nested sampling for physical scientists. Nature Reviews Methods Primers. 2022 Dec 31;2(1):39. Epub 2022 May 26. doi: 10.1038/s43586-022-00121-x

Author

Ashton, Greg ; Bernstein, Noam ; Buchner, Johannes et al. / Nested sampling for physical scientists. In: Nature Reviews Methods Primers. 2022 ; Vol. 2, No. 1.

Bibtex

@article{faea1e986a084fb19f248a4a19a37bac,
title = "Nested sampling for physical scientists",
abstract = "This Primer examines Skilling{\textquoteright}s nested sampling algorithm for Bayesian inference and, more broadly, multidimensional integration. The principles of nested sampling are summarized and recent developments using efficient nested sampling algorithms in high dimensions surveyed, including methods for sampling from the constrained prior. Different ways of applying nested sampling are outlined, with detailed examples from three scientific fields: cosmology, gravitational-wave astronomy and materials science. Finally, the Primer includes recommendations for best practices and a discussion of potential limitations and optimizations of nested sampling.",
author = "Greg Ashton and Noam Bernstein and Johannes Buchner and Xi Chen and G{\'a}bor Cs{\'a}nyi and Andrew Fowlie and Farhan Feroz and Matthew Griffiths and Will Handley and Michael Habeck and Edward Higson and Michael Hobson and Anthony Lasenby and David Parkinson and P{\'a}rtay, {Livia B.} and Matthew Pitkin and Doris Schneider and Speagle, {Joshua S.} and Leah South and John Veitch and Philipp Wacker and Wales, {David J.} and David Yallup",
note = "The Author's Accepted Manuscript (the accepted version of the manuscript as submitted by the author) may only be posted 6 months after the paper is published, consistent with our self-archiving embargo. Please note that the Author{\textquoteright}s Accepted Manuscript may not be released under a Creative Commons license. For Nature Research Terms of Reuse of archived manuscripts please see: http://www.nature.com/authors/policies/license.html#terms ",
year = "2022",
month = dec,
day = "31",
doi = "10.1038/s43586-022-00121-x",
language = "English",
volume = "2",
journal = "Nature Reviews Methods Primers",
issn = "2662-8449",
publisher = "Springer Science and Business Media LLC",
number = "1",

}

RIS

TY - JOUR

T1 - Nested sampling for physical scientists

AU - Ashton, Greg

AU - Bernstein, Noam

AU - Buchner, Johannes

AU - Chen, Xi

AU - Csányi, Gábor

AU - Fowlie, Andrew

AU - Feroz, Farhan

AU - Griffiths, Matthew

AU - Handley, Will

AU - Habeck, Michael

AU - Higson, Edward

AU - Hobson, Michael

AU - Lasenby, Anthony

AU - Parkinson, David

AU - Pártay, Livia B.

AU - Pitkin, Matthew

AU - Schneider, Doris

AU - Speagle, Joshua S.

AU - South, Leah

AU - Veitch, John

AU - Wacker, Philipp

AU - Wales, David J.

AU - Yallup, David

N1 - The Author's Accepted Manuscript (the accepted version of the manuscript as submitted by the author) may only be posted 6 months after the paper is published, consistent with our self-archiving embargo. Please note that the Author’s Accepted Manuscript may not be released under a Creative Commons license. For Nature Research Terms of Reuse of archived manuscripts please see: http://www.nature.com/authors/policies/license.html#terms

PY - 2022/12/31

Y1 - 2022/12/31

N2 - This Primer examines Skilling’s nested sampling algorithm for Bayesian inference and, more broadly, multidimensional integration. The principles of nested sampling are summarized and recent developments using efficient nested sampling algorithms in high dimensions surveyed, including methods for sampling from the constrained prior. Different ways of applying nested sampling are outlined, with detailed examples from three scientific fields: cosmology, gravitational-wave astronomy and materials science. Finally, the Primer includes recommendations for best practices and a discussion of potential limitations and optimizations of nested sampling.

AB - This Primer examines Skilling’s nested sampling algorithm for Bayesian inference and, more broadly, multidimensional integration. The principles of nested sampling are summarized and recent developments using efficient nested sampling algorithms in high dimensions surveyed, including methods for sampling from the constrained prior. Different ways of applying nested sampling are outlined, with detailed examples from three scientific fields: cosmology, gravitational-wave astronomy and materials science. Finally, the Primer includes recommendations for best practices and a discussion of potential limitations and optimizations of nested sampling.

U2 - 10.1038/s43586-022-00121-x

DO - 10.1038/s43586-022-00121-x

M3 - Journal article

VL - 2

JO - Nature Reviews Methods Primers

JF - Nature Reviews Methods Primers

SN - 2662-8449

IS - 1

M1 - 39

ER -