Introduction to worldwide earthquake probability distributions
Modelling the seismicity data is extremely difficult; hence, the assumptions on the distribution of earthquake occurrences play a crucial part in determining seismic hazard. Due to its simplicity and ease of use, the Poisson distribution has been the most common distribution for modelling earthquake...
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| Main Authors: | , |
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| Format: | Conference or Workshop Item |
| Language: | English |
| Subjects: | |
| Online Access: | http://eprints.um.edu.my/35233/1/Dr.%20Nur%20Anisah%20Mohamed%20%40%20A.%20Rahman%209.2022.pdf http://eprints.um.edu.my/35233/ |
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| Summary: | Modelling the seismicity data is extremely difficult; hence, the assumptions on the distribution of earthquake occurrences play a crucial part in determining seismic hazard. Due to its simplicity and ease of use, the Poisson distribution has been the most common distribution for modelling earthquake data over the past year. Nevertheless, the Poisson distribution appears inefficient due to the diversity of earthquake data and the temporal correlations that are common in many real earthquake sequences. The statistical goodness-of-fit tests using worldwide seismicity data from 1921 to 2021 indicate that earthquake temporal
occurrences do not always match the commonly used Poisson distribution in earthquake research. On the other hand, the Negative Binomial distribution was discovered to be a better distribution for observed earthquake magnitude distributions, and it may be applied in seismic analysis. |
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