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>.
Package details |
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Maintainer | |
License | GPL (>=3) |
Version | 1.2.4 |
URL | https://github.com/jtimonen/lgpr |
Package repository | View on GitHub |
Installation |
Install the latest version of this package by entering the following in R:
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