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lgpr: Longitudinal Gaussian Process Regression
Interpretable nonparametric modeling of longitudinal data using additive Gaussian process regression. Contains functionality for inferring covariate effects and assessing covariate relevances. Models are specified using a convenient formula syntax, and can include shared, group-specific, non-stationary, heterogeneous and temporally uncertain effects. Bayesian inference for model parameters is performed using 'Stan'. The modeling approach and methods are described in detail in Timonen et al. (2021) <doi:10.1093/bioinformatics/btab021>.
Getting started
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Package details |
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| Author | Juho Timonen [aut, cre] (<https://orcid.org/0000-0003-2341-6765>), Andrew Johnson [ctb] |
| Maintainer | Juho Timonen <juho.timonen@iki.fi> |
| License | GPL (>= 3) |
| Version | 1.2.4 |
| URL | https://github.com/jtimonen/lgpr |
| Package repository | View on CRAN |
| Installation |
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