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  "Title": "Intelligent Ranked Set Sampling with 'Excel' Integration and SRS\nComparison",
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  "Authors@R": "person(\"Khalid Ul Islam\", \"Rather\", email = \"drkhalidulislam@gmail.com\", role = c(\"aut\", \"cre\"))",
  "Description": "Provides tools for Ranked Set Sampling (RSS) analysis,\ndata import, statistical estimation, and comparison with Simple\nRandom Sampling (SRS). The package offers a complete workflow\nfrom 'Excel' and CSV data import and cleaning to RSS\nimplementation, efficiency evaluation, visualization, and\nautomated reporting. Intelligent ranking procedures based on\ncorrelation analysis, regression models, and machine learning\nmethods are included to address imperfect ranking commonly\nencountered in practical RSS applications. Monte Carlo\nsimulation tools are provided for evaluating estimator\nperformance under different sampling scenarios. Ranked Set\nSampling was originally introduced by McIntyre (1952)\n<doi:10.2307/3001960> as an efficient alternative to simple\nrandom sampling when ranking information is available at low\ncost. The package supports researchers, statisticians, and\npractitioners working in agricultural, environmental,\nbiological, and other applied sciences.",
  "License": "GPL-3",
  "Encoding": "UTF-8",
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  "Maintainer": "Khalid Ul Islam Rather <drkhalidulislam@gmail.com>",
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      "title": "Complete RSS Analysis",
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      "title": "Compare RSS and SRS",
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      "title": "Ranked Set Sampling",
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    },
    {
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      "title": "True Ranked Set Sampling (RSS)",
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