Package: binGroup 2.2-1

Frank Schaarschmidt

binGroup: Evaluation and Experimental Design for Binomial Group Testing

Methods for estimation and hypothesis testing of proportions in group testing designs: methods for estimating a proportion in a single population (assuming sensitivity and specificity equal to 1 in designs with equal group sizes), as well as hypothesis tests and functions for experimental design for this situation. For estimating one proportion or the difference of proportions, a number of confidence interval methods are included, which can deal with various different pool sizes. Further, regression methods are implemented for simple pooling and matrix pooling designs. Methods for identification of positive items in group testing designs: Optimal testing configurations can be found for hierarchical and array-based algorithms. Operating characteristics can be calculated for testing configurations across a wide variety of situations.

Authors:Boan Zhang [aut], Christopher Bilder [aut], Brad Biggerstaff [aut], Frank Schaarschmidt [aut, cre], Brianna Hitt [aut]

binGroup_2.2-1.tar.gz
binGroup_2.2-1.tar.gz(r-4.5-noble)binGroup_2.2-1.tar.gz(r-4.4-noble)
binGroup_2.2-1.tgz(r-4.4-emscripten)binGroup_2.2-1.tgz(r-4.3-emscripten)
binGroup.pdf |binGroup.html
binGroup/json (API)

# Install 'binGroup' in R:
install.packages('binGroup', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org'))

Peer review:

Datasets:
  • hivsurv - Data from an HIV surveillance project

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

3.09 score 101 scripts 1.5k downloads 8 mentions 56 exports 7 dependencies

Last updated 6 years agofrom:288a6aa03e. Checks:OK: 2. Indexed: yes.

TargetResultDate
Doc / VignettesOKNov 03 2024
R-4.5-linuxOKNov 03 2024

Exports:accuracy.dorfArray.Measuresbeta.distbgtCIbgtPowerbgtTestbgtvsbgtWidthbinACbinBlakerbinCIbinCPbinDesignbinPowerbinSOCbinTestbinWaldbinWidthbinWilsoncharacteristics.poolEMEM.halvingEM.mpEM.retestDesigngt.controlgtreggtreg.fitgtreg.halvinggtreg.mphierarchical.desc2Inf.ArrayInf.D3Inf.Dorfinf.dorf.measuresInformative.array.probMasterPool.Array.MeasuresnDesignNI.A2MNI.ArrayNI.D3NI.Dorfopt.info.dorfopt.pool.sizeOTCp.vec.funcpool.specific.dorfpooledBinpooledBinDiffpredict.gtresiduals.gtsDesignsim.gtsim.halvingsim.mpthresh.val.dorf

Dependencies:gmpmathjaxrpartitionspolynomrbibutilsRdpacksets

Readme and manuals

Help Manual

Help pageTopics
Statistical Methods for Group Testing.binGroup-package binGroup
Accuracy measures for informative Dorfman testingaccuracy.dorf
Operating characteristics for array testing without master poolingArray.Measures
Expected value of order statistics from a beta distributionbeta.dist
Confidence Intervals for One Proportion in Binomial Group TestingbgtAC bgtBlaker bgtCI bgtCP bgtSOC bgtWald bgtWilson
Power to Reject a Hypothesis in Binomial Group Testing for One ProportionbgtPower bgtPowerI
Hypothesis Test for One Proportion in Binomial Group TestingbgtTest
Confidence Interval for One Proportion in Group Testing with Variable Group Sizesbgtvs
Expected Width of Confidence Intervals in Binomial Group TestingbgtWidth bgtWidthI
Confidence Intervals for One Binomial ProportionbinAC binBlaker binCI binCP binSOC binWald binWilson
Sample Size Iteration for One Parameter Binomial ProblembinDesign
Power Calculation for One Parameter Binomial ProblembinPower binPowerI
Hypothesis tests for One Binomial ProportionbinTest
Expected Confidence Interval Width for One Binomial ProportionbinWidth
Testing expenditure for informative Dorfman testingcharacteristics.pool
Sample Size Iteration Depending on Minimal MSE in One-Parameter Group TestingestDesign msep
Auxiliary for Controlling Group Testing Regressiongt.control
Fitting Group Testing ModelsEM EM.ret gtreg gtreg.fit
Fitting Group Testing Models Under the Halving ProtocolEM.halving gtreg.halving
Fitting Group Testing Models in Matrix Pooling SettingEM.mp gtreg.mp
Operating characteristics for hierarchical group testinghierarchical.desc2
Data from an HIV surveillance projecthivsurv
Find the optimal testing configuration for informative array testing without master poolingInf.Array
Find the optimal testing configuration for informative three-stage hierarchical testingInf.D3
Find the optimal testing configuration for informative two-stage hierarchical (Dorfman) testingInf.Dorf
Operating characteristics for informative two-stage hierarchical (Dorfman) testinginf.dorf.measures
Arrange a matrix of probabilities for informative array testingInformative.array.prob
Operating characteristics for array testing with master poolingMasterPool.Array.Measures
Iterate Sample Size in One Parameter Group TestingnDesign
Find the optimal testing configuration for non-informative array testing with master poolingNI.A2M
Find the optimal testing configuration for non-informative array testing without master poolingNI.Array
Find the optimal testing configuration for non-informative three-stage hierarchical testingNI.D3
Find the optimal testing configuration for non-informative two-stage hierarchical testingNI.Dorf
Find the characteristics of an informative two-stage hierarchical (Dorfman) algorithmopt.info.dorf
Find the optimal pool size for Optimal Dorfman or Thresholded Optimal Dorfmanopt.pool.size
Find the optimal testing configurationOTC
Generate a vector of probabilities for informative group testing algorithms.p.vec.func
Plot Results of nDesign or sDesignplot.nDesign plot.sDesign
Plot Results of binDesignplot.binDesign
Diagnostic line fit for pool.bin objectsplot.poolbin
Find the optimal pool sizes for Pool-Specific Optimal Dorfman (PSOD) testingpool.specific.dorf
Confidence intervals for a single proportionpooledBin
Confidence intervals for the difference of proportionspooledBinDiff
Predict Method for Group Testing Model Fitspredict.gt
Print Functions for Group Testing CIs and Tests for One Proportionprint.bgtCI print.bgtTest print.bgtvs print.binCI print.binTest
Print Functions for nDesign and sDesignprint.nDesign print.sDesign
Print Function for binDesignprint.binDesign
Print methods for objects of classes "gt" and "gt.mp"print.gt
Print methods for classes "poolbin" and "poolbindiff"print.poolbin print.poolbindiff
Print Functions for summary.gt.mp and summary.gtprint.summary.gt print.summary.gt.mp
Extract Model Residuals From a Fitted Group Testing Modelresiduals.gt
Iterate Group Size for a One-Parameter Group Testing ProblemsDesign
Simulation Function for Group Testing Datasim.gt
Simulation Function for Group Testing Data for the Halving Protocolsim.halving
Simulation Function for Group Testing Data with Matrix Pooling Designsim.mp
Summary Method for Group Testing Model (Simple Pooling) Fitssummary.gt
Summary Method for Group Testing Model (Matrix Pooling) Fitssummary.gt.mp
Summary methods for "poolbin" and "poolbindiff"summary.poolbin summary.poolbindiff
Find the optimal threshold value for Thresholded Optimal Dorfman testingthresh.val.dorf