Identification and Estimation using Group Testing

Methods for the group testing identification problem: 1) Operating characteristics (e.g., expected number of tests) for commonly used hierarchical and array-based algorithms, and 2) Optimal testing configurations for these same algorithms. Calculations for algorithms with single-disease assays are described in Hitt et al. (2019) and with multiplex assays are described in Bilder et al. (2019) and Hou et al. (2020) . Methods for the group testing estimation problem: 1) Estimation and inference procedures for an overall prevalence, and 2) Regression modeling for commonly used hierarchical and array-based algorithms. Estimation and confidence interval methods are described in Biggerstaff (2008) and Hepworth & Biggerstaff (2017) . Regression modeling is described in Xie (2001) .


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1.1.0 by Brianna Hitt, a month ago

Browse source code at

Authors: Brianna Hitt [aut, cre] , Christopher Bilder [aut] , Frank Schaarschmidt [aut] , Brad Biggerstaff [aut] , Christopher McMahan [aut] , Joshua Tebbs [aut] , Boan Zhang [ctb] , Michael Black [ctb] , Peijie Hou [ctb] , Peng Chen [ctb]

Documentation:   PDF Manual  

GPL (>= 3) license

Imports ggplot2, graphics, grDevices, partitions, rBeta2009, Rcpp, Rdpack, scales, stats, utils

Linking to Rcpp, RcppArmadillo

See at CRAN