recipe r-corncob

Statistical modeling for correlated count data using the beta-binomial distribution, described in Martin et al. (2020) <doi:10.1214/19-AOAS1283>. It allows for both mean and overdispersion covariates.

Homepage:

https://github.com/bryandmartin/corncob

License:

GPL2 / GPL-2.0-or-later

Recipe:

/r-corncob/meta.yaml

package r-corncob

versions:

0.4.1-0,  0.3.2-0,  0.3.1-2,  0.3.1-1,  0.3.1-0,  0.3.0-1,  0.3.0-0,  0.2.0-0

depends r-base:

>=4.3,<4.4.0a0

depends r-detectseparation:

depends r-dplyr:

depends r-ggplot2:

depends r-magrittr:

depends r-numderiv:

depends r-rlang:

depends r-scales:

depends r-trust:

depends r-vgam:

requirements:

Installation

You need a conda-compatible package manager (currently either micromamba, mamba, or conda) and the Bioconda channel already activated (see set-up-channels).

While any of above package managers is fine, it is currently recommended to use either micromamba or mamba (see here for installation instructions). We will show all commands using mamba below, but the arguments are the same for the two others.

Given that you already have a conda environment in which you want to have this package, install with:

   mamba install r-corncob

and update with::

   mamba update r-corncob

To create a new environment, run:

mamba create --name myenvname r-corncob

with myenvname being a reasonable name for the environment (see e.g. the mamba docs for details and further options).

Alternatively, use the docker container:

   docker pull quay.io/biocontainers/r-corncob:<tag>

(see `r-corncob/tags`_ for valid values for ``<tag>``)

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