Forecasting Eruptions at Poorly Known Volcanoes Using Analogs and Multivariate Renewal Processes-Reference-Cited by-同舟云学术

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Forecasting Eruptions at Poorly Known Volcanoes Using Analogs and Multivariate Renewal Processes

Published:2022-06-14 Issue:12 Volume:49 Page:
ISSN:0094-8276
Container-title:Geophysical Research Letters
language:en
Short-container-title:Geophysical Research Letters

Author:

Wang Ting¹^ORCID,Bebbington Mark²^ORCID,Cronin Shane³^ORCID,Carman Joel¹

Affiliation:

1. Department of Mathematics and Statistics University of Otago Dunedin New Zealand

2. School of Mathematical and Computational Sciences, and School of Agriculture and Environment Massey University Palmerston North New Zealand

3. School of Environment University of Auckland Auckland New Zealand

Funder

Ministry of Business, Innovation and Employment

Publisher

American Geophysical Union (AGU)

Subject

General Earth and Planetary Sciences,Geophysics

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1029/2021GL096715

Reference55 articles.

1. Statistical analysis of repeated events forming renewal processes

2. Implications of silicic vent patterns for the presence of large crustal magma chambers

3. Trends and clustering in the onsets of volcanic eruptions

4. Long-term forecasting of volcanic explosivity

5. Spatio-temporal hazard estimation in the Auckland Volcanic Field, New Zealand, with a new event-order model

Cited by 2 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Identifying analogues for data-limited volcanoes using hierarchical clustering and expert knowledge: a case study of Melimoyu (Chile);Frontiers in Earth Science;2023-05-24

2. A simple two-state model interprets temporal modulations in eruptive activity and enhances multivolcano hazard quantification;Science Advances;2022-11-04

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