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Unbiased clustering estimation in the presence of missing observations

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Unbiased clustering estimation in the presence of missing observations. / Bianchi, Davide; Percival, Will J.

In: Monthly Notices of the Royal Astronomical Society, Vol. 472, No. 1, 11.2017, p. 1106–1118.

Research output: Contribution to journalArticlepeer-review

Harvard

Bianchi, D & Percival, WJ 2017, 'Unbiased clustering estimation in the presence of missing observations', Monthly Notices of the Royal Astronomical Society, vol. 472, no. 1, pp. 1106–1118. https://doi.org/10.1093/mnras/stx2053

APA

Bianchi, D., & Percival, W. J. (2017). Unbiased clustering estimation in the presence of missing observations. Monthly Notices of the Royal Astronomical Society, 472(1), 1106–1118. https://doi.org/10.1093/mnras/stx2053

Vancouver

Bianchi D, Percival WJ. Unbiased clustering estimation in the presence of missing observations. Monthly Notices of the Royal Astronomical Society. 2017 Nov;472(1):1106–1118. https://doi.org/10.1093/mnras/stx2053

Author

Bianchi, Davide ; Percival, Will J. / Unbiased clustering estimation in the presence of missing observations. In: Monthly Notices of the Royal Astronomical Society. 2017 ; Vol. 472, No. 1. pp. 1106–1118.

Bibtex

@article{286c8f7b116f45019f133a51def17d35,
title = "Unbiased clustering estimation in the presence of missing observations",
abstract = "In order to be efficient, spectroscopic galaxy redshift surveys do not obtain redshifts for all galaxies in the population targeted. The missing galaxies are often clustered, commonly leading to a lower proportion of successful observations in dense regions. One example is the close-pair issue for SDSS spectroscopic galaxy surveys, which have a deficit of pairs of observed galaxies with angular separation closer than the hardware limit on placing neighbouring fibers. Spatially clustered missing observations will exist in the next generations of surveys. Various schemes have previously been suggested to mitigate these effects, but none works for all situations. We argue that the solution is to link the missing galaxies to those observed with statistically equivalent clustering properties, and that the best way to do this is to rerun the targeting algorithm, varying the angular position of the observations. Provided that every pair has a non-zero probability of being observed in one realisation of the algorithm, then a pair-upweighting scheme linking targets to successful observations, can correct these issues. We present such a scheme, and demonstrate its validity using realisations of an idealised simple survey strategy.",
keywords = "astro-ph.CO, RCUK, STFC, ST/N000668/1, ST/N00180X/1",
author = "Davide Bianchi and Percival, {Will J.}",
note = "14 pages, 8 figures, published in MNRAS",
year = "2017",
month = nov,
doi = "10.1093/mnras/stx2053",
language = "English",
volume = "472",
pages = "1106–1118",
journal = "MNRAS",
issn = "0035-8711",
publisher = "Oxford University Press",
number = "1",

}

RIS

TY - JOUR

T1 - Unbiased clustering estimation in the presence of missing observations

AU - Bianchi, Davide

AU - Percival, Will J.

N1 - 14 pages, 8 figures, published in MNRAS

PY - 2017/11

Y1 - 2017/11

N2 - In order to be efficient, spectroscopic galaxy redshift surveys do not obtain redshifts for all galaxies in the population targeted. The missing galaxies are often clustered, commonly leading to a lower proportion of successful observations in dense regions. One example is the close-pair issue for SDSS spectroscopic galaxy surveys, which have a deficit of pairs of observed galaxies with angular separation closer than the hardware limit on placing neighbouring fibers. Spatially clustered missing observations will exist in the next generations of surveys. Various schemes have previously been suggested to mitigate these effects, but none works for all situations. We argue that the solution is to link the missing galaxies to those observed with statistically equivalent clustering properties, and that the best way to do this is to rerun the targeting algorithm, varying the angular position of the observations. Provided that every pair has a non-zero probability of being observed in one realisation of the algorithm, then a pair-upweighting scheme linking targets to successful observations, can correct these issues. We present such a scheme, and demonstrate its validity using realisations of an idealised simple survey strategy.

AB - In order to be efficient, spectroscopic galaxy redshift surveys do not obtain redshifts for all galaxies in the population targeted. The missing galaxies are often clustered, commonly leading to a lower proportion of successful observations in dense regions. One example is the close-pair issue for SDSS spectroscopic galaxy surveys, which have a deficit of pairs of observed galaxies with angular separation closer than the hardware limit on placing neighbouring fibers. Spatially clustered missing observations will exist in the next generations of surveys. Various schemes have previously been suggested to mitigate these effects, but none works for all situations. We argue that the solution is to link the missing galaxies to those observed with statistically equivalent clustering properties, and that the best way to do this is to rerun the targeting algorithm, varying the angular position of the observations. Provided that every pair has a non-zero probability of being observed in one realisation of the algorithm, then a pair-upweighting scheme linking targets to successful observations, can correct these issues. We present such a scheme, and demonstrate its validity using realisations of an idealised simple survey strategy.

KW - astro-ph.CO

KW - RCUK

KW - STFC

KW - ST/N000668/1

KW - ST/N00180X/1

U2 - 10.1093/mnras/stx2053

DO - 10.1093/mnras/stx2053

M3 - Article

VL - 472

SP - 1106

EP - 1118

JO - MNRAS

JF - MNRAS

SN - 0035-8711

IS - 1

ER -

ID: 7699318