step

Implementation of No-Effect-Concentration estimation that uses 'brms' (see Burkner (2017)<doi:10.18637/jss.v080.i01>; Burkner (2018)<doi:10.32614/RJ-2018-017>; Carpenter 'et al.' (2017)<doi: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)<doi:10.1016/j.ecoenv.2009.09.012>), 'NSEC' (see Fisher and Fox (2023)<doi:10.1002/etc.5610>), and 'N(S)EC (see Fisher et al. 2023<doi:10.1002/ieam.4809>). A full description of this package can be found in Fisher 'et al.' (2024)<doi: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)<doi:10.5281/ZENODO.3966864>).

Rebecca Fisher

bayesnec

A Bayesian No-Effect- Concentration (NEC) Algorithm

Diego R. Barneche

Gerard F. Ricardo

David R. Fox

step function

<dl><dt>x</dt>
<dd>A <code><a href="/link/numeric?package=bayesnec&version=2.1.3.0" data-mini-rdoc="bayesnec::numeric">numeric</a></code> vector.
the new range of values in x.</dd></dl>

Arguments

step — step

<dl>

<dt>x</dt>
<dd>A <code><a href='https://rdrr.io/r/base/numeric.html'>numeric</a></code> vector.
the new range of values in x.</dd>

</dl>

step: step

Description

Usage

Value

Arguments

Details