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  "Package": "generalRSS",
  "Title": "Statistical Tools for Balanced and Unbalanced Ranked Set\nSampling",
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  "Authors@R": "c(person(\"Soohyun\", \"Ahn\", email = \"shahn@ajou.ac.kr\", role = c(\"aut\", \"cre\")),\nperson(\"Chul\", \"Moon\", email = \"chulm@mail.smu.edu\", role = \"aut\"))",
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  "Description": "Ranked Set Sampling (RSS) is a stratified sampling method\nknown for its efficiency compared to Simple Random Sampling\n(SRS). When sample allocation is equal across strata, it is\nreferred to as balanced RSS (BRSS) whereas unequal allocation\nis called unbalanced RSS (URSS), which is particularly\neffective for asymmetric or skewed distributions. This package\noffers practical statistical tools and sampling methods for\nboth BRSS and URSS, emphasizing flexible sampling designs and\ninference for population means, medians, proportions, and Area\nUnder the Curve (AUC). It incorporates parametric and\nnonparametric tests, including empirical likelihood ratio (LR)\nmethods. The package provides ranked set sampling methods from\na given population, including sampling with imperfect ranking\nusing auxiliary variables. Furthermore, it provides tools for\nefficient sample allocation in URSS, ensuring greater\nefficiency than SRS and BRSS. For more details, refer e.g. to\nChen et al. (2003) <doi:10.1007/978-0-387-21664-5>, Ahn et al.\n(2022) <doi:10.1007/978-3-031-14525-4_3>, and Ahn et al. (2024)\n<doi:10.1111/insr.12589>.",
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  "Encoding": "UTF-8",
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  "Repository": "https://shahn63.r-universe.dev",
  "Date/Publication": "2025-09-12 07:47:38 UTC",
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      "title": "Generate ranked set samples for proportions",
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      ]
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      "title": "Generate ranked set samples",
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      ]
    },
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      "title": "RSS Sign test",
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