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>.
| Version: |
1.1.5 |
| Depends: |
R (≥ 3.4.0), methods |
| Imports: |
Rcpp (≥ 0.12.0), RcppParallel (≥ 5.0.2), RCurl (≥ 1.98), rstan (≥ 2.21.2), rstantools (≥ 2.1.1), bayesplot (≥ 1.7.0), MASS (≥ 7.3-50), stats (≥ 3.4), ggplot2 (≥ 3.1.0), gridExtra (≥ 0.3.0) |
| LinkingTo: |
BH (≥ 1.75.0-0), Rcpp (≥ 1.0.6), RcppEigen (≥ 0.3.3.9.1), RcppParallel (≥ 5.0.2), rstan (≥ 2.21.2), StanHeaders (≥
2.21.0-7) |
| Suggests: |
knitr, rmarkdown, testthat, covr |
| Published: |
2021-09-23 |
| Author: |
Juho Timonen 
[aut, cre] |
| Maintainer: |
Juho Timonen <juho.timonen at iki.fi> |
| BugReports: |
https://github.com/jtimonen/lgpr/issues |
| License: |
GPL (≥ 3) |
| URL: |
https://github.com/jtimonen/lgpr |
| NeedsCompilation: |
yes |
| SystemRequirements: |
GNU make |
| Citation: |
lgpr citation info |
| Materials: |
README |
| CRAN checks: |
lgpr results |
Documentation:
Downloads:
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