
Advanced methods for a valuable quantitative environmental risk assessment using Bayesian inference with several type of ecotoxicological data: 'binary' (e.g., survival, mobility), 'count' (e.g., reproduction) and 'continuous' (e.g., growth rate, length, weight).
library(remotes)
remotes::install_gitlab("mosaic-software/morsedr", host = "gitlab.in2p3.fr")
Before a submission, you can look at prepare-for-cran , which is an open and collaborative list of things you have to check before submitting your package to the CRAN.
Otherwise, check "as-cran"" using the source package:
library(devtools)
# create documentation
devtools::document(roclets = c('rd', 'collate', 'namespace'))
Once the archive is done, check that '.Rbuildignore' was applied properly. Try to have a low size archive (< 2Mb)
Either directly
# build and check the archive
devtools::check()
Or in 2 steps:
# 1. build the package.
devtools::build()
# 2. check the archive.
devtools::check_built("../morseDR_0.1.1.tar.gz")
See the CRAN status of your sumbmission: - incoming R CRAN packages: Index of /incoming - incoming dashboard: incoming dashboard
library('devtools')
devtools::document(roclets = c('rd', 'collate', 'namespace'))
devtools::build_manual()
From R session
library(covr)
cov <- package_coverage("morseDR")
data: load the data set.BinaryData, CountData or ContinuousData: make a ModelData object for binary, count and quantitative continuous data, respectively. data.frameplot: plot a ModelData object.summary: provides a summary of a ModelData object. doseResponse: return a DoseResponse object.plot: plot a DoseResponse object.fit: fit a ModelData object and return a Fit object.plot: plot a Fit object.ppc: return a PPC object.plot: plot a PPC object.Object: BigCamelCase
class(x) <- append("ObjectCamelCase", class(x))
Methods: small_snake_case
methods_snake_case.ObjectCamelCase <- function(...){}
Function (no methods - not linked to object): smallCamelCase
smallCamelCase <- function(...){}
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