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lgpr: an interpretable non-parametric method for inferring covariate effects from longitudinal data
MOTIVATION: Longitudinal study designs are indispensable for studying disease progression. Inferring covariate effects from longitudinal data, however, requires interpretable methods that can model complicated covariance structures and detect non-linear effects of both categorical and continuous cov...
| Autores principales: | , , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
Oxford University Press
2021
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| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8317115/ https://www.ncbi.nlm.nih.gov/pubmed/33471072 http://dx.doi.org/10.1093/bioinformatics/btab021 |