Package: gtDesign 0.1.1

gtDesign: Convex Optimal Designs for Group Testing Experiments

Finite candidate-set approximate optimal designs for group testing and related experiments, using convex optimization and equivalence checks. Implements the information matrix and cost structure for the prevalence / sensitivity / specificity model used in Huang and colleagues (2020), as in Chi-Kuang Yeh, Weng Kee Wong, and Julie Zhou (<doi:10.48550/arXiv.2508.08445>).

Authors:Chi-Kuang Yeh [aut, cre], Julie Zhou [aut], Weng Kee Wong [ctb]

gtDesign_0.1.1.tar.gz
gtDesign_0.1.1.zip(r-4.7-any)gtDesign_0.1.1.zip(r-4.6-any)gtDesign_0.1.1.zip(r-4.5-any)
gtDesign_0.1.1.tgz(r-4.6-any)gtDesign_0.1.1.tgz(r-4.5-any)
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gtDesign_0.1.1.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION
card.svg |card.png
gtDesign/json (API)

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

Bug tracker:https://github.com/chikuang/gtdesign/issues

On CRAN:

Conda:

group-testingoptimal-design

3.40 score 5 scripts 251 downloads 26 exports 25 dependencies

Last updated from:8134181077. Checks:9 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-develOK173
source / vignettesOK210
linux-releaseOK203
macos-releaseOK260
macos-oldrelOK257
windows-develOK121
windows-releaseOK97
windows-oldrelOK136
wasm-releaseOK130

Exports:calc_Aoptcalc_coptcalc_directional_derivativescalc_Doptcalc_Eoptcalc_eta_weights_maximincalc_multi_directional_derivativecheck_equivalencecheck_equivalence_maximincompute_design_SOcompute_maximin_designexact_design_efficiency_maximingt_huang2020_costgt_huang2020_fgt_huang2020_lambdagt_huang2020_pigt_huang2020_regressormaximin_design_workflowplot_equivalenceplot_equivalence_maximinround_gt_design_budgetround_gt_design_budget_maximinround_gt_design_n_maximinround_gt_design_subject_budgetrounding_budget_combinationsrounding_run_size_combinations

Dependencies:backportscheckmateclarabelcliCVXRgluegmphighslatticelifecyclemagrittrMASSMatrixosqppillarpkgconfigRcppRcppEigenrlangS7scsslamtibbleutf8vctrs

Readme and manuals

Help Manual

Help pageTopics
A-optimal approximate design for group testing experimentscalc_Aopt
c-optimal approximate design for group testing experimentscalc_copt
Directional derivatives on a finite candidate setcalc_directional_derivatives
D-optimal approximate design for group testing experimentscalc_Dopt
E-optimal approximate design for group testing experimentscalc_Eopt
Eta weights for the maximin equivalence theoremcalc_eta_weights_maximin
Weighted multi-objective directional derivativecalc_multi_directional_derivative
Check the equivalence theorem on a finite candidate setcheck_equivalence
Check the equivalence theorem for a maximin designcheck_equivalence_maximin
Single-objective optimal approximate design (group testing)compute_design_SO
Maximin multi-criterion approximate design (group testing)compute_maximin_design
Efficiencies of an exact design relative to single-objective optima (maximin)exact_design_efficiency_maximin
Standardized cost for pool size (Huang et al. 2020)gt_huang2020_cost
Gradient vector \mathbf{f}(x) for the Huang et al. (2020) modelgt_huang2020_f
Weight lambda(x) in the information matrix (Huang et al. 2020)gt_huang2020_lambda
Positive test probability (Huang et al. 2020 / arXiv:2508.08445 Sec. 2)gt_huang2020_pi
Effective regressor sqrt{lambda(x)}\,\mathbf{f}(x) for convex design codegt_huang2020_regressor
Maximin design with reference losses, equivalence, and eta (workflow)maximin_design_workflow
Plot equivalence theorem directional derivativeplot_equivalence
Plot equivalence diagnostics for a maximin designplot_equivalence_maximin
Exact group-testing design under a fixed budget (Rounding Algorithm II)round_gt_design_budget
Exact maximin design under fixed budget (Algorithm II + search)round_gt_design_budget_maximin
Exact maximin design under fixed run size (Algorithm I + search)round_gt_design_n_maximin
Exact design under subject-count constraint via budget roundinground_gt_design_subject_budget
Enumerate budget-feasible integer allocations (cost-aware rounding)rounding_budget_combinations
Enumerate nonnegative integer allocations (run-size rounding)rounding_run_size_combinations