Flexible Distributed Lag Models for Count Data Using mgcv.

In this tutorial we present the use of R package mgcv to implement Distributed Lag Non-Linear Models (DLNMs) in a flexible way. Interpretation of smoothing splines as random quantities enables approximate Bayesian inference, which in turn allows uncertainty quantification and comprehensive model che...

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Bibliographic Details

Published in:	American Statistician Vol. 79; no. 3; pp. 371 - 383
Main Authors:	Economou, Theo, Parliari, Daphne, Tobias, Aurelio, Dawkins, Laura, Steptoe, Hamish, Sarran, Christophe, Stoner, Oliver, Lowe, Rachel, Lelieveld, Jos
Format:	Article
Published:	Taylor & Francis Ltd Aug2025
Subjects:	Epidemiology Statistical models Spatial variation Mixture distributions (Probability theory) Bayesian analysis
Online Access:	View this record in EBSCOhost