An additive Gaussian process regression model for interpretable non-parametric analysis of longitudinal data

Biomedical research typically involves longitudinal study designs where samples from individuals are measured repeatedly over time and the goal is to identify risk factors (covariates) that are associated with an outcome value. General linear mixed effect models are the standard workhorse for statis...

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Detalles Bibliográficos
Autores principales: Cheng, Lu, Ramchandran, Siddharth, Vatanen, Tommi, Lietzén, Niina, Lahesmaa, Riitta, Vehtari, Aki, Lähdesmäki, Harri
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2019
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6470127/
https://www.ncbi.nlm.nih.gov/pubmed/30996266
http://dx.doi.org/10.1038/s41467-019-09785-8

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6470127/
https://www.ncbi.nlm.nih.gov/pubmed/30996266
http://dx.doi.org/10.1038/s41467-019-09785-8

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