bayesnec

Implementation of No-Effect-Concentration estimation that uses 'brms' (see Burkner (2017)[https://doi.org/10.18637/jss.v080.i01]; Burkner (2018)[https://doi.org/10.32614/RJ-2018-017]; Carpenter 'et al.' (2017)[https://doi.org/10.18637/jss.v076.i01] to fit concentration(dose)-response data using Bayesian methods for the purpose of estimating 'ECx' values, but more particularly 'NEC' (see Fox (2010)[https://doi.org/10.1016/j.ecoenv.2009.09.012]), 'NSEC' (see Fisher and Fox (2023)[https://doi.org/10.1002/etc.5610]), and 'N(S)EC (see Fisher et al. 2023[https://doi.org/10.1002/ieam.4809]). A full description of this package can be found in Fisher 'et al.' (2024)[https://doi.org/10.18637/jss.v110.i05]. This package expands and supersedes an original version implemented in 'R2jags' (see Su and Yajima (2020)[https://CRAN.R-project.org/package=R2jags]; Fisher et al. (2020)[https://doi.org/10.5281/ZENODO.3966864]).

Last 30 days

This package has been downloaded 406 times in the last 30 days. Enough downloads to make a small wave in the niche community. The curiosity is spreading! The following heatmap shows the distribution of downloads per day. Yesterday, it was downloaded 3 times.

The following line graph shows the downloads per day. You can hover over the graph to see the exact number of downloads per day.

Last 365 days

This package has been downloaded 5,429 times in the last 365 days. That's a lot of interest! Someone might even write a blog post about it. The day with the most downloads was Jul 21, 2024 with 133 downloads.

The following line graph shows the downloads per day. You can hover over the graph to see the exact number of downloads per day.