Gutenberg–Richter B-Value Time Series Forecasting: A Weighted Likelihood Approach

Gutenberg–Richter B-Value Time Series Forecasting: A Weighted Likelihood Approach

We introduce a novel approach to estimate the temporal variation of the b-value parameter of the Gutenberg–Richter law, based on the weighted likelihood approach. This methodology allows estimating the b-value based on the full history of the available data, within a data-driven setting. We test thi...

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Bibliographic Details
Main Authors: Matteo Taroni, Giorgio Vocalelli, Andrea De Polis
Format: Article
Language:English
Published: MDPI AG 2021-08-01
Series:Forecasting
Subjects:
earthquake forecasting
time-series analysis
statistical seismology
Online Access:https://www.mdpi.com/2571-9394/3/3/35
Description
Summary:We introduce a novel approach to estimate the temporal variation of the b-value parameter of the Gutenberg–Richter law, based on the weighted likelihood approach. This methodology allows estimating the b-value based on the full history of the available data, within a data-driven setting. We test this methodology against the classical “rolling window” approach using a high-definition Italian seismic catalogue as well as a global catalogue of high magnitudes. The weighted likelihood approach outperforms competing methods, and measures the optimal amount of past information relevant to the estimation.
ISSN:2571-9394

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