Graph sampling by lagged random walk
Peer reviewed, Journal article
Accepted version

View/ Open
Date
2021-12-10Metadata
Show full item recordCollections
- Artikler / Journal articles [426]
- Publikasjoner fra Cristin [138]
Original version
Zhang, L.-C. (2022). Graph sampling by lagged random walk. Stat, 11( 1), e444. https://doi.org/10.1002/sta4.444 10.1002/sta4.444Abstract
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.
Description
"This is the peer reviewed version of the following article: Zhang, L.-C. (2022). Graph sampling by lagged random walk. Stat, 11( 1), e444, which has been published in final form at https://doi.org/10.1002/sta4.444
This article may be used for non-commercial purposes in accordance with Wiley Terms and Conditions for Use of Self-Archived Versions. This article may not be enhanced, enriched or otherwise transformed into a derivative work, without express permission from Wiley or by statutory rights under applicable legislation. Copyright notices must not be removed, obscured or modified. The article must be linked to Wiley’s version of record on Wiley Online Library and any embedding, framing or otherwise making available the article or pages thereof by third parties from platforms, services and websites other than Wiley Online Library must be prohibited."