Graph sampling by lagged random walk
Graph sampling by lagged random walk
We propose a family of lagged random walk sampling methods in simple undirected graphs, where transition to the next state (i.e. node) depends on both the current and previous states---hence, lagged. The existing random walk sampling methods can be incorporated as special cases. We develop a novel approach to estimation based on lagged random walks at equilibrium, where the target parameter can be any function of values associated with finite-order subgraphs, such as edge, triangle, 4-cycle and others.
Zhang, Li-Chun
a5d48518-7f71-4ed9-bdcb-6585c2da3649
25 April 2022
Zhang, Li-Chun
a5d48518-7f71-4ed9-bdcb-6585c2da3649
Abstract
We propose a family of lagged random walk sampling methods in simple undirected graphs, where transition to the next state (i.e. node) depends on both the current and previous states---hence, lagged. The existing random walk sampling methods can be incorporated as special cases. We develop a novel approach to estimation based on lagged random walks at equilibrium, where the target parameter can be any function of values associated with finite-order subgraphs, such as edge, triangle, 4-cycle and others.
Text
LRWsamplingR1
- Accepted Manuscript
More information
Accepted/In Press date: 3 December 2021
e-pub ahead of print date: 10 December 2021
Published date: 25 April 2022
Identifiers
Local EPrints ID: 453108
URI: http://eprints.soton.ac.uk/id/eprint/453108
ISSN: 2049-1573
PURE UUID: d39bda4f-1f39-46a8-be5a-e0b56088949a
Catalogue record
Date deposited: 08 Jan 2022 21:29
Last modified: 17 Mar 2024 07:00
Export record
Altmetrics
Download statistics
Downloads from ePrints over the past year. Other digital versions may also be available to download e.g. from the publisher's website.
View more statistics
