Package: nbfar 0.1
Aditya Mishra
nbfar: Negative Binomial Factor Regression Models ('nbfar')
We developed a negative binomial factor regression model to estimate structured (sparse) associations between a feature matrix X and overdispersed count data Y. With 'nbfar', microbiome count data Y can be used, for example, to associate host or environmental covariates with microbial abundances. Currently, two models are available: a) Negative Binomial reduced rank regression (NB-RRR), b) Negative Binomial co-sparse factor regression (NB-FAR). Please refer the manuscript 'Mishra, A. K., & Müller, C. L. (2021). Negative Binomial factor regression with application to microbiome data analysis. bioRxiv.' for more details.
Authors:
nbfar_0.1.tar.gz
nbfar_0.1.tar.gz(r-4.5-noble)nbfar_0.1.tar.gz(r-4.4-noble)
nbfar_0.1.tgz(r-4.4-emscripten)nbfar_0.1.tgz(r-4.3-emscripten)
nbfar.pdf |nbfar.html✨
nbfar/json (API)
# Install 'nbfar' in R: |
install.packages('nbfar', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/amishra-stats/nbfar/issues
Last updated 3 years agofrom:92e078ea69. Checks:OK: 1 WARNING: 1. Indexed: no.
Target | Result | Date |
---|---|---|
Doc / Vignettes | OK | Dec 23 2024 |
R-4.5-linux-x86_64 | WARNING | Dec 23 2024 |
Exports:nbfarnbfar_controlnbfar_simnbrrr
Dependencies:bstclicodetoolscolorspacedoParallelfansifarverforeachgbmggplot2glmnetgluegtableisobanditeratorslabelinglatticelifecyclemagrittrMASSMatrixmgcvmpathmunsellnlmenumDerivpillarpkgconfigpsclR6RColorBrewerRcppRcppArmadilloRcppEigenRcppParallelrlangrpartrrpackscalesshapesurvivaltibbleutf8vctrsviridisLiteWeightSVMwithr