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  "Title": "Convex Optimal Designs for Group Testing Experiments",
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  "Description": "Finite candidate-set approximate optimal designs for group\ntesting and related experiments, using convex optimization and\nequivalence checks. Implements the information matrix and cost\nstructure for the prevalence / sensitivity / specificity model\nused in Huang and colleagues (2020), as in Chi-Kuang Yeh, Weng\nKee Wong, and Julie Zhou (<doi:10.48550/arXiv.2508.08445>).",
  "URL": "https://github.com/chikuang/gtDesign,\nhttps://arxiv.org/abs/2508.08445",
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  "Repository": "https://chikuang.r-universe.dev",
  "Date/Publication": "2026-09-02 03:25:33 UTC",
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    "gt_huang2020_f",
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    "gt_huang2020_regressor",
    "maximin_design_workflow",
    "plot_equivalence",
    "plot_equivalence_maximin",
    "round_gt_design_budget",
    "round_gt_design_budget_maximin",
    "round_gt_design_n_maximin",
    "round_gt_design_subject_budget",
    "rounding_budget_combinations",
    "rounding_run_size_combinations"
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      "page": "calc_Aopt",
      "title": "A-optimal approximate design for group testing experiments",
      "topics": [
        "calc_Aopt"
      ]
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    {
      "page": "calc_copt",
      "title": "c-optimal approximate design for group testing experiments",
      "topics": [
        "calc_copt"
      ]
    },
    {
      "page": "calc_directional_derivatives",
      "title": "Directional derivatives on a finite candidate set",
      "topics": [
        "calc_directional_derivatives"
      ]
    },
    {
      "page": "calc_Dopt",
      "title": "D-optimal approximate design for group testing experiments",
      "topics": [
        "calc_Dopt"
      ]
    },
    {
      "page": "calc_Eopt",
      "title": "E-optimal approximate design for group testing experiments",
      "topics": [
        "calc_Eopt"
      ]
    },
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      "page": "calc_eta_weights_maximin",
      "title": "Eta weights for the maximin equivalence theorem",
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        "calc_eta_weights_maximin"
      ]
    },
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      "page": "calc_multi_directional_derivative",
      "title": "Weighted multi-objective directional derivative",
      "topics": [
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    },
    {
      "page": "check_equivalence",
      "title": "Check the equivalence theorem on a finite candidate set",
      "topics": [
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    },
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      "page": "check_equivalence_maximin",
      "title": "Check the equivalence theorem for a maximin design",
      "topics": [
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      ]
    },
    {
      "page": "compute_design_SO",
      "title": "Single-objective optimal approximate design (group testing)",
      "topics": [
        "compute_design_SO"
      ]
    },
    {
      "page": "compute_maximin_design",
      "title": "Maximin multi-criterion approximate design (group testing)",
      "topics": [
        "compute_maximin_design"
      ]
    },
    {
      "page": "exact_design_efficiency_maximin",
      "title": "Efficiencies of an exact design relative to single-objective optima (maximin)",
      "topics": [
        "exact_design_efficiency_maximin"
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    },
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      "page": "gt_huang2020_cost",
      "title": "Standardized cost for pool size (Huang et al. 2020)",
      "topics": [
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    },
    {
      "page": "gt_huang2020_f",
      "title": "Gradient vector \\mathbf{f}(x) for the Huang et al. (2020) model",
      "topics": [
        "gt_huang2020_f"
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    },
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      "page": "gt_huang2020_lambda",
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      "title": "Positive test probability (Huang et al. 2020 / arXiv:2508.08445 Sec. 2)",
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      "title": "Plot equivalence theorem directional derivative",
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    },
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