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-4.5-noble)NBR_0.1.5.tar.gz(r-4.4-noble)
NBR_0.1.5.tgz(r-4.4-emscripten)NBR_0.1.5.tgz(r-4.3-emscripten)
NBR.pdf |NBR.html
NBR/json (API)

# Install 'NBR' in R:
install.packages('NBR', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org'))

Peer review:

Datasets:
  • frontal2D - Frontal lobe functional connectivity in ADHD
  • voles - Prairie voles functional connectivity

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

3.56 score 36 scripts 157 downloads 5 exports 2 dependencies

Last updated 2 years agofrom:a791eb84c7. Checks:OK: 2. Indexed: yes.

TargetResultDate
Doc / VignettesOKOct 31 2024
R-4.5-linuxOKOct 31 2024

Exports:edge_lmnbr_lmnbr_lm_aovnbr_lmenbr_lme_aov

Dependencies:latticenlme

Network-Based R-statistics for linear models

Rendered fromNBR-LM.Rmdusingknitr::rmarkdownon Oct 31 2024.

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

Network-Based R-statistics for mixed-effects models

Rendered fromNBR-LME.Rmdusingknitr::rmarkdownon Oct 31 2024.

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