Recent Releases of toxicr
toxicr - ToxicR v 1.1.0
This release updates the package to use the EFSA suite of continuous models. To install:
Depending on your system, cut and paste the following code into your R terminal.
Recommended Method
Compile Yourself
If you have the package devtools, you can download and install directly from GitHub!
library(devtools)
devtools::install_github("NIEHS/ToxicR")
Note: For Windows, you will need the rtools executable available at: https://cran.r-project.org/bin/windows/Rtools/
Note: If you have a MacOS, you will need to download the GNU Scientific Library. To do this, go to a command line and type
brew install gsl
This assumes you have HomeBrew installed. If you do not go to https://brew.sh, which will give you the instructions on how to install.
Note: For Linux, you will also need the GNU Scientific Library. The install depends on your flavor of Linux. For Ubuntu, type
sudo apt-get install libgsl-dev
Alternative Methodology
First, install the required packages
install.packages(c("Rcpp","RcppEigen","RcppGSL","ggplot2","shiny","coda","scales","tidyverse","forcats","ggridges","doBy","multcomp","dplyr","rmarkdown", "actuar","ggpubr", "testthat","gridExtra","VIM","knitr", "modules", "plotly" ))
Windows R 4.3.0
download.file("https://github.com/NIEHS/ToxicR/releases/download/v1.10.0r2/ToxicR_23.4.1.1.0R4.3.zip",
"ToxicR_23.4.1.1.0.zip")
install.packages("ToxicR_23.4.1.1.0.zip", repos = NULL, type = "win.binary")
Windows R 4.2.3
download.file("https://github.com/NIEHS/ToxicR/releases/download/v1.10.0r2/ToxicR_23.4.1.1.0R4.2.3.zip",
"ToxicR_23.4.1.1.0.zip")
install.packages("ToxicR_23.4.1.1.0.zip", repos = NULL, type = "win.binary")
MacOS R 4.3 (M1)
download.file("https://github.com/NIEHS/ToxicR/releases/download/v1.10.0r2/ToxicR_23.4.1.1.0.tgz",
"ToxicR_23.4.1.1.0.tgz")
install.packages("ToxicR_23.4.1.1.0.tgz", repos = NULL, type = "mac.binary")
- C++
Published by wheelemw about 3 years ago
toxicr - 23.4.1.1.0
This release updates the package to use the EFSA suite of continuous models. To install:
Depending on your system, cut and paste the following code into your R terminal.
Recommended Method
Compile Yourself
If you have the package devtools, you can download and install directly from GitHub!
library(devtools)
devtools::install_github("NIEHS/ToxicR")
Note: For Windows, you will need the rtools executable available at: https://cran.r-project.org/bin/windows/Rtools/
Note: If you have a MacOS, you will need to download the GNU Scientific Library. To do this, go to a command line and type
brew install gsl
This assumes you have HomeBrew installed. If you do not go to https://brew.sh, which will give you the instructions on how to install.
Note: For Linux, you will also need the GNU Scientific Library. The install depends on your flavor of Linux. For Ubuntu, type
sudo apt-get install libgsl-dev
Alternative Methodology
First, install the required packages
install.packages(c("Rcpp","RcppEigen","RcppGSL","ggplot2","shiny","coda","scales","tidyverse","forcats","ggridges","doBy","multcomp","dplyr","rmarkdown", "actuar","ggpubr", "testthat","gridExtra","VIM","knitr", "modules", "plotly" ))
Windows R 4.3.0
download.file("https://github.com/NIEHS/ToxicR/releases/download/v1.10.0/ToxicR_23.4.1.1.0.R4.3.zip",
"ToxicR_23.4.1.1.0.zip")
install.packages("ToxicR_23.4.1.1.0.zip", repos = NULL, type = "win.binary")
Windows R 4.2.3
download.file("https://github.com/NIEHS/ToxicR/releases/download/v1.10.0/ToxicR_23.4.1.1.0R4.2.3.zip",
"ToxicR_23.4.1.1.0.zip")
install.packages("ToxicR_23.4.1.1.0.zip", repos = NULL, type = "win.binary")
MacOS R 4.3 (M1)
download.file("https://github.com/NIEHS/ToxicR/releases/download/v1.10.0/ToxicR_23.4.1.1.0.tgz",
"ToxicR_23.4.1.1.0.tgz")
install.packages("ToxicR_23.4.1.1.0.tgz", repos = NULL, type = "mac.binary")
- C++
Published by wheelemw about 3 years ago
toxicr - Cumulative Fixes
There have been a number of deprecated C++ functions that flagged warnings on CRAN. This is a cumulative update changing those function calls. There is no new functionality since 22.8.1.0.2.
- C++
Published by wheelemw over 3 years ago
toxicr - ToxicR 22.8.1.02
Version 22.8.1.0.2
The following fixes are in version 1.0.2:
- Function 'single_continuous_fit' and 'ma_continuous_fit' changed error when defining default priors
for 'distribution=normal-ncv' when data are negative. Originally the variance was described as mean(Y)/var(Y);
however, for negative means, this causes NA error. It is now defined as abs(mean(Y))/var(Y).
- Log-normal distribution fits were incorrect when summarized data was used. The correct transformation of
summarized data is now performed. The formula for standard deviation was typed in as sqrt(log((sd)^2/mu + 1)) it is now sqrt(log((sd/mu)^2+1)).
- Changed default priors for dichotomous fits to be consistant with Wheeler et al. (2020).
The following changes to fitting were made:
- Changed MLE Polynomial fit behavior. Now the terms up to the quadratic are constrained to be in the direction
of the response. After this, i.e., degree >= 3, the parameters are unconstrained.
- Added summary and print methods for mcmc model averaging.
Known Problems not yet fixed
- GoF for MA individual models not given.
- GoF for dichotomous models with (0/1) data fails.
- C++
Published by wheelemw almost 4 years ago
toxicr - ToxicR 22.01 (1.0.0)
Initial Release of ToxicR 1/28/2022.
Executable files are for R 4.1.2 in Windows/Mac(Intel/M1). - The macOS release is single threaded due to OpenMP issues. - The Windows release is multi-threaded - For Linux compiles GSL (2.6 or greater) and NLOPT (2.4 or greater) libraries need to be installed.
Release Notes:
Dichotomous and Continuous Dose-Response functionality
Dichotomous - MLE functionality (Equivalent to EPA BMDS 3.x) - Bayesian MAP/Laplace (Equivalent to EPA BMDS 3.2+) - Bayesian MCMC estimates - Bayesian Model Averaging (MAP Equivalent to EPA BMDS 3.2+)
Continuous - MLE functionality (Equivalent to EPA BMDS 3.x) - Bayesian MAP/Laplace - Bayesian MCMC estimates - Bayesian Model Averaging
NTP Bioassay Tests - Dose Dependent Trend Tests (e.g. Williams etc) - PolyK Test
Methodologies Described in Bailer, A.J. and Portier, C.J., 1988. Effects of treatment-induced mortality and tumor-induced mortality on tests for carcinogenicity in small samples. Biometrics, pp.417-431.
Wheeler, M.W., Blessinger, T., Shao, K., Allen, B.C., Olszyk, L., Davis, J.A. and Gift, J.S., 2020. Quantitative Risk Assessment: Developing a Bayesian Approach to Dichotomous Dose–Response Uncertainty. Risk Analysis, 40(9), pp.1706-1722.
Wheeler, M.W. Cortinas,J. Aerts, M. Gift, J.S. Davis J.A., 2022. Continuous Model Averaging for Benchmark Dose Analysis: Averaging Over Distributional Forms. Resubmitted to Environmetrics.
- C++
Published by wheelemw over 4 years ago