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On admissibility in bipartite incidence graph sampling

On admissibility in bipartite incidence graph sampling
On admissibility in bipartite incidence graph sampling
n bipartite incidence graph sampling, the target study units may be formed as connected population elements, which are distinct to the units of sampling and there may exist generally more than one way by which a given study unit can be observed via sampling units. This generalizes finite-population element or multistage sampling, where each element can only be sampled directly or via a single primary sampling unit. We study the admissibility of estimators in bipartite incidence graph sampling, where a minimal level of knowledge is available of the connections between the sampling and study units to enable design-unbiased estimation. We prove that there exist many other admissible estimators than the classic Horvitz-Thompson estimator. Our result fills also a gap in the literature of unconventional finite-population sampling where other unbiased estimators provide alternatives to the Horvitz-Thompson estimator.
graph sampling, admissibility, ancestry knowledge, incidence weighting estimator
2325-0984
García-Segador, Pedro
e1f9cb3f-eec6-4ad5-9420-1fa70fc857aa
Zhang, Li-Chun
a5d48518-7f71-4ed9-bdcb-6585c2da3649
García-Segador, Pedro
e1f9cb3f-eec6-4ad5-9420-1fa70fc857aa
Zhang, Li-Chun
a5d48518-7f71-4ed9-bdcb-6585c2da3649

García-Segador, Pedro and Zhang, Li-Chun (2025) On admissibility in bipartite incidence graph sampling. Journal of Survey Statistics and Methodology. (In Press)

Record type: Article

Abstract

n bipartite incidence graph sampling, the target study units may be formed as connected population elements, which are distinct to the units of sampling and there may exist generally more than one way by which a given study unit can be observed via sampling units. This generalizes finite-population element or multistage sampling, where each element can only be sampled directly or via a single primary sampling unit. We study the admissibility of estimators in bipartite incidence graph sampling, where a minimal level of knowledge is available of the connections between the sampling and study units to enable design-unbiased estimation. We prove that there exist many other admissible estimators than the classic Horvitz-Thompson estimator. Our result fills also a gap in the literature of unconventional finite-population sampling where other unbiased estimators provide alternatives to the Horvitz-Thompson estimator.

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BIGS_admissibility_final - Accepted Manuscript
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More information

Accepted/In Press date: 28 September 2025
Keywords: graph sampling, admissibility, ancestry knowledge, incidence weighting estimator

Identifiers

Local EPrints ID: 506771
URI: http://eprints.soton.ac.uk/id/eprint/506771
ISSN: 2325-0984
PURE UUID: 4bfadada-f5b9-4940-9e62-18e88cddd2d7
ORCID for Li-Chun Zhang: ORCID iD orcid.org/0000-0002-3944-9484

Catalogue record

Date deposited: 18 Nov 2025 17:39
Last modified: 19 Nov 2025 02:45

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Contributors

Author: Pedro García-Segador
Author: Li-Chun Zhang ORCID iD

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