Package: NBR 0.1.5

Zeus Gracia-Tabuenca

NBR: Network-Based R-Statistics using Mixed Effects Models

An implementation of network-based statistics in R using mixed effects models. Theoretical background for Network-Based Statistics can be found in Zalesky et al. (2010) <doi:10.1016/j.neuroimage.2010.06.041>. For Mixed Effects Models check the R package <https://CRAN.R-project.org/package=nlme>.

Authors:Zeus Gracia-Tabuenca [aut, cre], Sarael Alcauter [aut]

NBR_0.1.5.tar.gz
NBR_0.1.5.tar.gz(r-4.7-any)NBR_0.1.5.tar.gz(r-4.6-any)
NBR_0.1.5.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION
card.svg |card.png
NBR/json (API)

# Install 'NBR' in R:
install.packages('NBR', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org'))
Datasets:
  • frontal2D - Frontal lobe functional connectivity in ADHD
  • voles - Prairie voles functional connectivity

On CRAN:

Conda:

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

3.36 score 23 scripts 265 downloads 5 exports 2 dependencies

Last updated from:a791eb84c7. Checks:4 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-devel-x86_64OK120
source / vignettesOK186
linux-release-x86_64OK116
wasm-releaseOK102

Exports:edge_lmnbr_lmnbr_lm_aovnbr_lmenbr_lme_aov

Dependencies:latticenlme

Network-Based R-statistics for linear models
Rendered fromNBR-LM.Rmdusingknitr::rmarkdown

Last update: 2022-01-31
Started: 2020-03-26

Network-Based R-statistics for mixed-effects models
Rendered fromNBR-LME.Rmdusingknitr::rmarkdown

Last update: 2022-01-31
Started: 2020-03-26