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Graph spatial sampling

Graph spatial sampling
Graph spatial sampling
We develop lagged Metropolis-Hastings walk for sampling from simple undirected graphs according to given stationary sampling probabilities. It is explained how the technique can be applied together with designed graphs for sampling of units-in-space. Compared to the existing spatial sampling methods, which chiefly focus on the sample spatial balance regardless of the associated outcomes of interest, the proposed graph spatial sampling method can considerably improve the efficiency because the graph can be designed to take into account the anticipated spatial distribution of the outcome of interest.
graph sampling, random tessellation, local pivotal method, spatial trend
2049-1573
Zhang, Li-Chun
a5d48518-7f71-4ed9-bdcb-6585c2da3649
Zhang, Li-Chun
a5d48518-7f71-4ed9-bdcb-6585c2da3649

Zhang, Li-Chun (2024) Graph spatial sampling. Stat.

Record type: Article

Abstract

We develop lagged Metropolis-Hastings walk for sampling from simple undirected graphs according to given stationary sampling probabilities. It is explained how the technique can be applied together with designed graphs for sampling of units-in-space. Compared to the existing spatial sampling methods, which chiefly focus on the sample spatial balance regardless of the associated outcomes of interest, the proposed graph spatial sampling method can considerably improve the efficiency because the graph can be designed to take into account the anticipated spatial distribution of the outcome of interest.

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Accepted/In Press date: 2 June 2024
Published date: 23 June 2024
Keywords: graph sampling, random tessellation, local pivotal method, spatial trend

Identifiers

Local EPrints ID: 490899
URI: http://eprints.soton.ac.uk/id/eprint/490899
ISSN: 2049-1573
PURE UUID: ed866d21-6aef-4378-ac16-97fa284d20df
ORCID for Li-Chun Zhang: ORCID iD orcid.org/0000-0002-3944-9484

Catalogue record

Date deposited: 07 Jun 2024 17:45
Last modified: 19 Nov 2024 02:44

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Contributors

Author: Li-Chun Zhang ORCID iD

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