Vignette Engine Wrapping IPython Notebooks
Calls the 'Jupyter'/'IPython' script 'nbconvert' to create vignettes from notebooks.
Those notebooks ('.ipynb' files) are files containing rich text, code, and its output.
Code cells can be edited and evaluated interactively.
See <http://ipython.org/notebook.html> for more information.
pandoc, ipython (>= 3.0) or jupyter,
ipython/jupyter notebook optional dependencies, pywin32 (on
windows)

Vignette Engine Wrapping Jupyter Notebooks
Calls the 'Jupyter' script 'nbconvert' to create vignettes from
notebooks. Those notebooks ('.ipynb' files) are files containing rich text,
code, and its output. Code cells can be edited and evaluated interactively.
See <https://jupyter.org/> for more information.
pandoc, jupyter, jupyter nbconvert ("nbconvert"
python package), pywin32 (on windows)

person(given = "Benjamin",
family = "Davies",
email = "dev@bldavies.com",
role = c("aut", "cre"),
comment = c(ORCID = "0000-0002-1749-4567"))
Catalogue of NBER working papers published between June 1973 and June 2021.
Benjamin Davies [aut, cre] (<https://orcid.org/0000-0002-1749-4567>)

Catalogue of NBER working papers published between June 1973 and December 2021.

Negative Binomial Factor Regression Models ('nbfar')
c(person(given = 'Aditya',
family = 'Mishra',
role = c('aut', 'cre'),
email = 'amishra@flatironinstitute.org'),
person(given = 'Christian',
family = 'Mueller',
role = 'aut'))
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.
Rcpp (>= 0.12.9), MASS, magrittr, rrpack, glmnet,
RcppParallel, mpath
Aditya Mishra [aut, cre],
Christian Mueller [aut]