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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Detalles Bibliográficos

Publicado en:	American Statistician Vol. 79; no. 3; pp. 371 - 383
Autores principales:	Economou, Theo, Parliari, Daphne, Tobias, Aurelio, Dawkins, Laura, Steptoe, Hamish, Sarran, Christophe, Stoner, Oliver, Lowe, Rachel, Lelieveld, Jos
Formato:	Artículo
Publicado:	Taylor & Francis Ltd Aug2025
Materias:	Epidemiology Statistical models Spatial variation Mixture distributions (Probability theory) Bayesian analysis
Acceso en línea:	Ver este registro en EBSCOhost