{ "_id": "6a1067d2acfb0bcc41ca943b", "Package": "spnaf", "Type": "Package", "Title": "Spatial Network Autocorrelation for Flow Data", "Version": "1.1.0", "Authors@R": "c(\nperson(given=\"Youngbin\", family=\"Lee\", email = \"youngbin@snu.ac.kr\", role = c(\"aut\", \"cre\"), comment = c(ORCID = \"0000-0003-3466-6495\")),\nperson(given=\"Hui Jeong\", family=\"Ha\", email=\"hailyeeha@gmail.com\", role=\"aut\", comment = c(ORCID = \"0000-0002-5229-4528\")),\nperson(given=\"Sohyun\", family=\"Park\", email=\"spark230@gmu.edu\", role=\"aut\", comment = c(ORCID = \"0000-0002-1231-5662\")),\nperson(given=\"Kyusik\", family=\"Kim\", email=\"wpkyusik@gmail.com\", role=\"aut\", comment = c(ORCID = \"0000-0003-3753-3196\")),\nperson(given=\"Jinhyung\", family=\"Lee\", email=\"jinhyung.lee@uwo.ca\", role=\"aut\", comment = c(ORCID = \"0000-0003-1859-3441\")))", "Description": "Identify statistically significant flow clusters using the\nlocal spatial network autocorrelation statistic G_ij* proposed\nby 'Berglund' and 'Karlström' (1999)\n. The metric, an extended statistic\nof 'Getis/Ord' G ('Getis' and 'Ord' 1992)\n, detects a group of\nflows having similar traits in terms of directionality. You\nprovide OD data and the associated polygon to get results with\nseveral parameters, some of which are defined by spdep package.", "License": "MIT + file LICENSE", "Encoding": "UTF-8", "LazyData": "true", "RoxygenNote": "7.3.1", "VignetteBuilder": "knitr", "NeedsCompilation": "no", "Packaged": { "Date": "2026-05-08 05:16:16 UTC", "User": "root" }, "Author": "Youngbin Lee [aut, cre]\n(), Hui Jeong Ha [aut]\n(), Sohyun Park [aut]\n(), Kyusik Kim [aut]\n(), Jinhyung Lee [aut]\n()", "Maintainer": "Youngbin Lee ", "Repository": "https://cran.r-universe.dev", "Date/Publication": "2024-07-29 02:48:25 UTC", "RemoteUrl": "https://github.com/cran/spnaf", "RemoteRef": "HEAD", "RemoteSha": "5aa246f65d3fe071aeed61a0b896f60f872821c3", "MD5sum": "765133a0ae49ea9c100230209b713c2d", "_user": "cran", "_type": "src", "_file": "spnaf_1.1.0.tar.gz", "_fileid": "0682136b6843ace251557c94ff27c9dcb28d0cab9b924eebe8b3a02b6a4bd7dc", "_filesize": 873010, "_sha256": 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