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  "Package": "SCCDdesign",
  "Title": "Construction of Screening Designs for Mixed Level Continuous and\nCategorical Factors",
  "Version": "0.2.0",
  "Authors@R": "c(\nperson(\"Vyshna\", \"I C\",\nemail = \"vyshnaic@gmail.com\",\nrole = c(\"aut\", \"cre\")),\nperson(\"Cini\", \"Varghese\",\nemail = \"Cini2204@gmail.com\",\nrole = c(\"aut\", \"ctb\")),\nperson(\"Safeela\", \"Nasrin\",\nemail = \"nasrinkareem315@gmail.com\",\nrole = \"aut\"),\nperson(\"Boyina\", \"Devi Priyanka\",\nemail = \"boyinadevipriyanka@gmail.com\",\nrole = c(\"aut\", \"ctb\")),\nperson(\"Mohd\", \"Harun\",\nemail = \"harun.agribhu@gmail.com\",\nrole = c(\"aut\", \"ctb\")),\nperson(\"Anindita\", \"Datta\",\nemail = \"aninditaiasri@gmail.com\",\nrole = c(\"aut\", \"ctb\"))\n)",
  "Description": "Constructs screening designs for experiments involving\ncontinuous and categorical factors with multiple levels. The\npackage implements methods for constructing mixed-level\nscreening designs, involving factors with more than two levels.\nIt also evaluates the statistical performance of screening\ndesigns throughdev power to identify active effects and Type I\nerror rates. The package implements three methods proposed by\nJones, B., Lekivetz, R., Majumdar, D. and Nachtsheim, C. (2025)\n<doi:10.1080/00401706.2024.2362149> for generating efficient\nscreening designs involving three-level continuous and\ntwo-level categorical factors for even run sizes. It also\nincludes Paley Type I and Type II constructions for conference\nmatrices and pseudo conference matrices obtained using the\ncoordinate exchange algorithm by Jones, B. and Nachtsheim, C.\nJ. (2011) <doi:10.1080/00224065.2011.11917841> which are used\nin the development of these screening designs.",
  "License": "GPL-3",
  "Encoding": "UTF-8",
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  "NeedsCompilation": "no",
  "Packaged": {
    "Date": "2026-09-21 17:19:41 UTC",
    "User": "root"
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  "Author": "Vyshna I C [aut, cre], Cini Varghese [aut, ctb], Safeela Nasrin\n[aut], Boyina Devi Priyanka [aut, ctb], Mohd Harun [aut, ctb],\nAnindita Datta [aut, ctb]",
  "Maintainer": "Vyshna I C <vyshnaic@gmail.com>",
  "Repository": "https://cran.r-universe.dev",
  "Date/Publication": "2026-09-21 10:00:41 UTC",
  "RemoteUrl": "https://github.com/cran/SCCDdesign",
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  "_created": "2026-09-21T17:19:41.000Z",
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    "dOptimalTwoLevel",
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    "mixed_level_design",
    "pseudoConference",
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      "page": "conferenceMatrix",
      "title": "Constructs a conference matrix of a specified order using a direct construction for order 2 and Paley-based constructions for supported odd prime or prime-power values of q = n - 1.",
      "topics": [
        "conferenceMatrix"
      ]
    },
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      "title": "Constructs a D-optimal two-level design with 'm' runs and 'm - 1' factors. The factor levels are coded as -1 and +1.",
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      ]
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      "title": "Constructs a Hadamard matrix of order 'n' using 'pracma::hadamard()'.",
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      ]
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      "title": "Constructs an orthogonal design for two types of factors with different numbers of levels. Three construction cases are considered: even-even level factors, odd-even level factors and odd-odd level factors. The appropriate construction is selected automatically according to the parity of the numbers of levels of the two factors. Hadamard matrices are used for even-level factors, while conference matrices are used for odd-level factors. The order of both the Hadamard and conference matrices is 'm'. For the even-even case, the design contains 'm - 1' factors of each type. For the odd-even case, the design contains 'm' odd-level factors and 'm - 1' even-level factors. For the odd-odd case, the design contains 'm' factors of each type.",
      "topics": [
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      ]
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      "title": "Constructs a pseudo-conference matrix of order 'n' using a determinant-based search procedure.",
      "topics": [
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      ]
    },
    {
      "page": "SCCD",
      "title": "Constructs an SCCD for a specified number of runs (n=2m). The construction method is selected automatically according to the number of runs.",
      "topics": [
        "SCCD"
      ]
    },
    {
      "page": "simulation",
      "title": "Performs a simulation study to evaluate the ability of a design to identify active main effects using best-subsets regression and the AICc criterion.",
      "topics": [
        "simulation"
      ]
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