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Flexible distributed lags for modelling earthquake data
Author(s) -
Obermeier Viola,
Scheipl Fabian,
Heumann Christian,
Wassermann Joachim,
Küchenhoff Helmut
Publication year - 2015
Publication title -
journal of the royal statistical society: series c (applied statistics)
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.205
H-Index - 72
eISSN - 1467-9876
pISSN - 0035-9254
DOI - 10.1111/rssc.12077
Subject(s) - generalized additive model , computer science , lag , spline (mechanical) , distributed lag , inference , data mining , algorithm , engineering , artificial intelligence , machine learning , structural engineering , computer network
Summary Heavy long‐lasting rainfall can trigger earthquake swarms. We are interested in the specific shape of lagged rain influence on the occurrence of earthquakes at different depths at Mount Hochstaufen, Bavaria. We present a novel penalty structure for interpretable and flexible estimates of lag coefficients based on spline representations. We provide an easy‐to‐use implementation of our flexible distributed lag approach that can be used directly in the established R package mgcv for estimation of generalized additive models. This allows our approach to be immediately included in complex additive models for generalized responses even in hierarchical or longitudinal data settings, making use of established stable and well‐tested inference algorithms. The benefit of flexible distributed lag modelling is shown in a detailed simulation study.