CRAN/E | lgpr

lgpr

Longitudinal Gaussian Process Regression

Installation

About

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.

Citation lgpr citation info
github.com/jtimonen/lgpr
System requirements GNU make
Bug report File report

Key Metrics

Version 1.2.4
R ≥ 3.4.0
Published 2023-09-24 187 days ago
Needs compilation? yes
License GPL (≥ 3)
CRAN checks lgpr results

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Maintainer

Maintainer

Juho Timonen

juho.timonen@iki.fi

Authors

Juho Timonen

aut / cre

Andrew Johnson

ctb

Material

README
Reference manual
Package source

Vignettes

Mathematical description of lgpr models

macOS

r-release

arm64

r-oldrel

arm64

r-release

x86_64

r-oldrel

x86_64

Windows

r-devel

x86_64

r-release

x86_64

r-oldrel

x86_64

Old Sources

lgpr archive

Depends

R ≥ 3.4.0
methods

Imports

Rcpp ≥ 0.12.0
RcppParallel ≥ 5.0.2
RCurl ≥ 1.98
rstan ≥ 2.26.0
rstantools ≥ 2.3.1
bayesplot ≥ 1.7.0
MASS ≥ 7.3-50
stats ≥ 3.4
ggplot2 ≥ 3.1.0
gridExtra ≥ 0.3.0

Suggests

knitr
rmarkdown
testthat
covr

LinkingTo

BH ≥ 1.75.0-0
Rcpp ≥ 1.0.6
RcppEigen ≥ 0.3.3.9.1
RcppParallel ≥ 5.0.2
rstan ≥ 2.26.0
StanHeaders ≥2.26.0