Simultaneous Truth and Performance Level Estimation
An implementation of Simultaneous Truth and
Performance Level Estimation (STAPLE) . This
method is used when there are multiple raters for an object, typically an
image, and this method fuses these ratings into one rating. It uses an
expectation-maximization method to estimate this rating and the individual
specificity/sensitivity for each rater.
The goal of stapler is to provide an implementation of Simultaneous
Truth and Performance Level Estimation (STAPLE), where there are
multiple raters for an object.
Installation
You can install stapler from GitHub with:
# install.packages("remotes")
remotes::install_github("muschellij2/stapler")
News
stapler 0.6.6
Added RNGversion for sampling. Will update in future.
stapler 0.6.5
Added checks for dimensions.
stapler 0.6.3
Fixed DESCRIPTION file for CRAN.
stapler 0.6.2
First Submission to CRAN
staple function now main function to be used
Added a NEWS.md file to track changes to the package.