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  "Title": "Density Estimation for Point-Centered Quarter Method with\nTruncated Sampling",
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  "Authors@R": "c(\nperson(given = \"Wenzhe\", family = \"Huang\", role = c(\"aut\", \"cre\"),\nemail = \"51280155097@stu.ecnu.edu.cn\"),\nperson(given = \"Guochun\", family = \"Shen\", role = \"aut\"),\nperson(given = \"Dingliang\", family = \"Xing\", role = \"aut\"),\nperson(given = \"Jiangyan\", family = \"Zhao\", role = \"aut\")\n)",
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  "Description": "Implements a systematic methodology for estimating\npopulation density from point-centered quarter method (PCQM)\nsurveys when distance measurements are truncated by a maximum\nsearch radius (right-censored). The package provides a unified\nframework for analyzing such incomplete data, addressing both\ncompletely randomly distributed (Poisson) and spatially\naggregated (Negative Binomial) populations. Key features\ninclude: (1) Adjusted moment-based density estimators for\ncensored distances; (2) Maximum likelihood estimation (MLE) of\ndensity under the Poisson (CSR) model; and (3) Simultaneous MLE\nof density and an aggregation parameter under the Negative\nBinomial model. For more details, see Huang, Shen, Xing, and\nZhao (2026) <doi:10.48550/arXiv.2603.08276>.",
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  "Date/Publication": "2026-05-27 08:58:30 UTC",
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