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bayesnec  

A Bayesian No-Effect- Concentration (NEC) Algorithm
View on CRAN: Click here


Download and install bayesnec package within the R console
Install from CRAN:
install.packages("bayesnec")

Install from Github:
library("remotes")
install_github("cran/bayesnec")

Install by package version:
library("remotes")
install_version("bayesnec", "2.1.3.0")



Attach the package and use:
library("bayesnec")
Maintained by
Rebecca Fisher
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2021-07-02
Latest Update: 2023-03-29
Description:
Implementation of No-Effect-Concentration estimation that uses 'brms' (see Burkner (2017); Burkner (2018); Carpenter 'et al.' (2017) to fit concentration(dose)-response data using Bayesian methods for the purpose of estimating 'ECx' values, but more particularly 'NEC' (see Fox (2010)), 'NSEC' (see Fisher and Fox (2023)), and 'N(S)EC (see Fisher et al. 2023). This package expands and supersedes an original version implemented in R2jags, see Fisher, Ricardo and Fox (2020).
How to cite:
Rebecca Fisher (2021). bayesnec: A Bayesian No-Effect- Concentration (NEC) Algorithm. R package version 2.1.3.0, https://cran.r-project.org/web/packages/bayesnec. Accessed 22 Dec. 2024.
Previous versions and publish date:
1.0.1 (2021-07-02 09:00), 2.0.1 (2021-09-20 10:00), 2.0.2.3 (2022-03-28 09:50), 2.0.2.4 (2022-04-21 13:20), 2.0.2.5 (2022-10-31 09:00), 2.0.2 (2021-10-17 08:20), 2.0 (2021-09-16 07:10), 2.1.0.0 (2022-12-15 07:40), 2.1.0.1 (2023-02-07 07:32), 2.1.0.2 (2023-02-21 01:30), 2.1.0.3 (2023-03-29 15:50), 2.1.1.0 (2023-09-26 08:50), 2.1.2.0 (2024-03-28 16:50)
Other packages that cited bayesnec R package
View bayesnec citation profile
Other R packages that bayesnec depends, imports, suggests or enhances
Complete documentation for bayesnec
Functions, R codes and Examples using the bayesnec R package
Some associated functions: amend . autoplot . average_endpoints . average_estimates . bayesmanecfit-class . bayesnec-package . bayesnecfit-class . bayesnecformula . beta_binomial2 . beta_binomial2_lpmf . beta_binomial2_rng . bnec . bnec_newdata . bnecfit-class . c.bnecfit . check_chains . check_formula . check_priors . compare_endpoints . compare_estimates . compare_fitted . compare_posterior . dispersion . ecx . expand_manec . expand_nec . fitted . formula . ggbnec_data . herbicide . is_manecsummary . is_necsummary . log_lik_beta_binomial2 . make_brmsformula . manec_example . manecsummary-class . model.frame . models . nec . nec_data . necsummary-class . nsec . plot . plus-.bnecfit . posterior_epred . posterior_epred_beta_binomial2 . posterior_predict . posterior_predict_beta_binomial2 . prebayesnecfit-class . predict . print . pull_brmsfit . pull_out . pull_prior . quote-beta_binomial-quote . rhat . sample_priors . show_params . summary . update.bnecfit . 
Some associated R codes: add_criteria.R . amend.R . autoplot.R . average_endpoints.R . average_estimates.R . bayesmanecfit-class.R . bayesnec-package.R . bayesnecfit-class.R . bayesnecformula.R . beta_binomial2.R . bnec.R . bnec_newdata.R . bnecfit-class.R . bnecfit-methods.R . capture_family.R . check_chains.R . check_data.R . check_models.R . check_priors.R . compare_endpoints.R . compare_estimates.R . compare_fitted.R . compare_posterior.R . data.R . define_prior.R . dispersion.R . ecx.R . expand_classes.R . extract_simdat.R . fit_bayesnec.R . fitted.R . formula.R . helpers.R . inits_functions.R . manecsummary-class.R . model.frame.R . models.R . nec.R . necsummary-class.R . nsec.R . plot.R . posterior_epred.R . posterior_predict.R . prebayesnecfit-class.R . pred_equations.R . predict.R . print.R . pull_brmsfit.R . pull_out.R . pull_prior.R . rhat.R . sample_priors.R . set_distribution.R . show_params.R . summary.R . validate_family.R . validate_loo_controls.R . validate_priors.R .  Full bayesnec package functions and examples
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