A test for checking earthquake aperiodicity estimates from small samples
In recent years, many new models for earthquake recurrence were proposed. Some are focusing on the clustering properties on a small time scale, while others try to model the long term behavior of large mainshocks. To this last purpose, there is a growing interest for models that take into account th...
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doaj-f582b52a9c7c4831873027d828cc957b2020-11-25T01:43:02ZengCopernicus PublicationsNatural Hazards and Earth System Sciences1561-86331684-99812007-06-0173399404A test for checking earthquake aperiodicity estimates from small samplesM. MucciarelliIn recent years, many new models for earthquake recurrence were proposed. Some are focusing on the clustering properties on a small time scale, while others try to model the long term behavior of large mainshocks. To this last purpose, there is a growing interest for models that take into account the aperiodicity aiming to a time-dependent hazard estimate. It is well known that a limited number of inter-event times (IETs) may lead to biased values of the distribution parameters. To overcome this problem different solutions were proposed. This paper focuses on two of them: Monte Carlo simulation of the process and aperiodicity estimated via a statistical proxy. The topics discussed are: 1) how many IETs are needed for a correct estimate, 2) to which extent a Poisson distribution is equally able to describe the process, 3) the influence of errors associated to paleoseismological IETs, and 4) the goodness of the success ratio from simulations. A simple test is proposed to discriminate real aperiodicity from apparent aperiodicity coming from undersampling. http://www.nat-hazards-earth-syst-sci.net/7/399/2007/nhess-7-399-2007.pdf |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
M. Mucciarelli |
spellingShingle |
M. Mucciarelli A test for checking earthquake aperiodicity estimates from small samples Natural Hazards and Earth System Sciences |
author_facet |
M. Mucciarelli |
author_sort |
M. Mucciarelli |
title |
A test for checking earthquake aperiodicity estimates from small samples |
title_short |
A test for checking earthquake aperiodicity estimates from small samples |
title_full |
A test for checking earthquake aperiodicity estimates from small samples |
title_fullStr |
A test for checking earthquake aperiodicity estimates from small samples |
title_full_unstemmed |
A test for checking earthquake aperiodicity estimates from small samples |
title_sort |
test for checking earthquake aperiodicity estimates from small samples |
publisher |
Copernicus Publications |
series |
Natural Hazards and Earth System Sciences |
issn |
1561-8633 1684-9981 |
publishDate |
2007-06-01 |
description |
In recent years, many new models for earthquake recurrence were proposed. Some are focusing on the clustering properties on a small time scale, while others try to model the long term behavior of large mainshocks. To this last purpose, there is a growing interest for models that take into account the aperiodicity aiming to a time-dependent hazard estimate. It is well known that a limited number of inter-event times (IETs) may lead to biased values of the distribution parameters. To overcome this problem different solutions were proposed. This paper focuses on two of them: Monte Carlo simulation of the process and aperiodicity estimated via a statistical proxy. The topics discussed are: 1) how many IETs are needed for a correct estimate, 2) to which extent a Poisson distribution is equally able to describe the process, 3) the influence of errors associated to paleoseismological IETs, and 4) the goodness of the success ratio from simulations. A simple test is proposed to discriminate real aperiodicity from apparent aperiodicity coming from undersampling. |
url |
http://www.nat-hazards-earth-syst-sci.net/7/399/2007/nhess-7-399-2007.pdf |
work_keys_str_mv |
AT mmucciarelli atestforcheckingearthquakeaperiodicityestimatesfromsmallsamples AT mmucciarelli testforcheckingearthquakeaperiodicityestimatesfromsmallsamples |
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