{
  "_id": "6a26d9a824555f66ed524ec3",
  "Package": "NNS",
  "Type": "Package",
  "Title": "Nonlinear Nonparametric Statistics",
  "Version": "12.2",
  "Date": "2026-06-08",
  "Authors@R": "c(\nperson(\"Fred\", \"Viole\", role=c(\"aut\",\"cre\"), email=\"ovvo.open.source@gmail.com\"),\nperson(\"Roberto\", \"Spadim\", role=\"ctb\"),\nperson(\"Rasheed\", \"Khoshnaw\", role =\"ctb\")\n)",
  "Maintainer": "Fred Viole <ovvo.open.source@gmail.com>",
  "Description": "NNS (Nonlinear Nonparametric Statistics) leverages partial\nmoments – the fundamental elements of variance that\nasymptotically approximate the area under f(x) – to provide a\nrobust foundation for nonlinear analysis while maintaining\nlinear equivalences.  Designed for real-world data that\nviolates symmetry, linearity, or distributional assumptions,\nNNS delivers a comprehensive suite of advanced statistical\ntechniques, including: Numerical integration, Numerical\ndifferentiation, Clustering, Correlation, Dependence, Causal\nanalysis, ANOVA, Regression, Classification, Seasonality,\nAutoregressive modeling, Normalization, Stochastic superiority\n/ dominance and Advanced Monte Carlo sampling.  All routines\nbased on: Viole, F. and Nawrocki, D. (2013), Nonlinear\nNonparametric Statistics: Using Partial Moments (ISBN:\n1490523995, Second edition:\n<https://ovvo-financial.github.io/NNS/book/>).",
  "BugReports": "https://github.com/OVVO-Financial/NNS/issues",
  "License": "GPL-3",
  "URL": "https://github.com/OVVO-Financial/NNS",
  "VignetteBuilder": "knitr",
  "SystemRequirements": "GNU make",
  "Config/testthat/edition": "3",
  "RoxygenNote": "7.2.3",
  "Encoding": "UTF-8",
  "Config/pak/sysreqs": "cmake libfreetype6-dev libglu1-mesa-dev make\ntexlive libpng-dev libuv1-dev libgl1-mesa-dev zlib1g-dev",
  "Repository": "https://ovvo-financial.r-universe.dev",
  "Date/Publication": "2026-06-08 14:37:06 UTC",
  "RemoteUrl": "https://github.com/ovvo-financial/nns",
  "RemoteRef": "HEAD",
  "RemoteSha": "0578c17dbbcb9786fb53719c40c7adcab038dd73",
  "NeedsCompilation": "yes",
  "Packaged": {
    "Date": "2026-06-08 14:53:46 UTC",
    "User": "root"
  },
  "Author": "Fred Viole [aut, cre],\nRoberto Spadim [ctb],\nRasheed Khoshnaw [ctb]",
  "MD5sum": "db5d1df4497a3b01edd0c188d8dffbc5",
  "_user": "ovvo-financial",
  "_type": "src",
  "_file": "NNS_12.2.tar.gz",
  "_fileid": "432259a654013ffcdc0efbc97b6c8cf4167e0c10ea994b0de708ab38d0dcfd66",
  "_filesize": 22412590,
  "_sha256": "432259a654013ffcdc0efbc97b6c8cf4167e0c10ea994b0de708ab38d0dcfd66",
  "_created": "2026-06-08T14:53:46.000Z",
  "_published": "2026-06-08T15:03:04.136Z",
  "_distro": "noble",
  "_jobs": [
    {
      "job": 80124825168,
      "time": 245,
      "config": "linux-devel-arm64",
      "r": "4.7.0",
      "check": "WARNING",
      "artifact": "7484052489"
    },
    {
      "job": 80124825523,
      "time": 269,
      "config": "linux-devel-x86_64",
      "r": "4.7.0",
      "check": "WARNING",
      "artifact": "7484061874"
    },
    {
      "job": 80124825208,
      "time": 243,
      "config": "linux-release-arm64",
      "r": "4.6.0",
      "check": "WARNING",
      "artifact": "7484052110"
    },
    {
      "job": 80124825172,
      "time": 223,
      "config": "linux-release-x86_64",
      "r": "4.6.0",
      "check": "WARNING",
      "artifact": "7484041533"
    },
    {
      "job": 80124825219,
      "time": 176,
      "config": "macos-oldrel-arm64",
      "r": "4.5.3",
      "check": "WARNING",
      "artifact": "7484139591"
    },
    {
      "job": 80124825186,
      "time": 267,
      "config": "macos-oldrel-x86_64",
      "r": "4.5.3",
      "check": "WARNING",
      "artifact": "7484102532"
    },
    {
      "job": 80124825369,
      "time": 161,
      "config": "macos-release-arm64",
      "r": "4.6.0",
      "check": "WARNING",
      "artifact": "7484059671"
    },
    {
      "job": 80124825333,
      "time": 371,
      "config": "macos-release-x86_64",
      "r": "4.6.0",
      "check": "WARNING",
      "artifact": "7484150917"
    },
    {
      "job": 80123538973,
      "time": 342,
      "config": "source",
      "r": "4.6.0",
      "check": "OK",
      "artifact": "7483937983"
    },
    {
      "job": 80124825084,
      "time": 185,
      "config": "wasm-release",
      "r": "4.6.0",
      "check": "OK",
      "artifact": "7484023677"
    },
    {
      "job": 80124825454,
      "time": 263,
      "config": "windows-devel",
      "r": "4.7.0",
      "check": "WARNING",
      "artifact": "7484059719"
    },
    {
      "job": 80124825157,
      "time": 230,
      "config": "windows-oldrel",
      "r": "4.5.3",
      "check": "WARNING",
      "artifact": "7484045487"
    },
    {
      "job": 80124825376,
      "time": 233,
      "config": "windows-release",
      "r": "4.6.0",
      "check": "WARNING",
      "artifact": "7484046329"
    }
  ],
  "_buildurl": "https://github.com/r-universe/ovvo-financial/actions/runs/27145904463",
  "_status": "success",
  "_host": "GitHub-Actions",
  "_upstream": "https://github.com/ovvo-financial/nns",
  "_commit": {
    "id": "0578c17dbbcb9786fb53719c40c7adcab038dd73",
    "author": "OVVO-Financial <ovvo.financialsystems@gmail.com>",
    "committer": "OVVO-Financial <ovvo.financialsystems@gmail.com>",
    "message": "NNS 12.2 Beta\n",
    "time": 1780929426
  },
  "_maintainer": {
    "name": "Fred Viole",
    "email": "ovvo.open.source@gmail.com"
  },
  "_registered": true,
  "_dependencies": [
    {
      "package": "R",
      "version": ">= 3.6.0",
      "role": "Depends"
    },
    {
      "package": "Rcpp",
      "role": "LinkingTo"
    },
    {
      "package": "RcppParallel",
      "role": "LinkingTo"
    },
    {
      "package": "data.table",
      "role": "Imports"
    },
    {
      "package": "doParallel",
      "role": "Imports"
    },
    {
      "package": "foreach",
      "role": "Imports"
    },
    {
      "package": "Rcpp",
      "role": "Imports"
    },
    {
      "package": "RcppParallel",
      "role": "Imports"
    },
    {
      "package": "Rfast",
      "role": "Imports"
    },
    {
      "package": "rgl",
      "role": "Imports"
    },
    {
      "package": "xts",
      "role": "Imports"
    },
    {
      "package": "zoo",
      "role": "Imports"
    },
    {
      "package": "knitr",
      "role": "Suggests"
    },
    {
      "package": "rmarkdown",
      "role": "Suggests"
    },
    {
      "package": "testthat",
      "version": ">= 3.0.0",
      "role": "Suggests"
    }
  ],
  "_owner": "ovvo-financial",
  "_selfowned": true,
  "_usedby": 3,
  "_updates": [
    {
      "week": "2025-28",
      "n": 6
    },
    {
      "week": "2025-29",
      "n": 4
    },
    {
      "week": "2025-30",
      "n": 10
    },
    {
      "week": "2025-31",
      "n": 8
    },
    {
      "week": "2025-32",
      "n": 8
    },
    {
      "week": "2025-33",
      "n": 7
    },
    {
      "week": "2025-34",
      "n": 12
    },
    {
      "week": "2025-35",
      "n": 1
    },
    {
      "week": "2025-36",
      "n": 7
    },
    {
      "week": "2025-37",
      "n": 7
    },
    {
      "week": "2025-38",
      "n": 4
    },
    {
      "week": "2025-40",
      "n": 10
    },
    {
      "week": "2025-41",
      "n": 3
    },
    {
      "week": "2025-42",
      "n": 1
    },
    {
      "week": "2025-46",
      "n": 3
    },
    {
      "week": "2025-48",
      "n": 2
    },
    {
      "week": "2025-49",
      "n": 1
    },
    {
      "week": "2026-02",
      "n": 3
    },
    {
      "week": "2026-03",
      "n": 2
    },
    {
      "week": "2026-05",
      "n": 1
    },
    {
      "week": "2026-07",
      "n": 2
    },
    {
      "week": "2026-08",
      "n": 4
    },
    {
      "week": "2026-09",
      "n": 9
    },
    {
      "week": "2026-10",
      "n": 2
    },
    {
      "week": "2026-11",
      "n": 4
    },
    {
      "week": "2026-12",
      "n": 12
    },
    {
      "week": "2026-13",
      "n": 16
    },
    {
      "week": "2026-14",
      "n": 18
    },
    {
      "week": "2026-15",
      "n": 11
    },
    {
      "week": "2026-16",
      "n": 2
    },
    {
      "week": "2026-20",
      "n": 10
    },
    {
      "week": "2026-21",
      "n": 6
    },
    {
      "week": "2026-23",
      "n": 14
    },
    {
      "week": "2026-24",
      "n": 2
    }
  ],
  "_tags": [],
  "_topics": [
    "clustering",
    "econometrics",
    "machine-learning",
    "nonlinear",
    "nonparametric",
    "partial-moments",
    "statistics",
    "time-series",
    "cpp"
  ],
  "_stars": 109,
  "_contributors": [
    {
      "user": "ovvo-financial",
      "count": 149,
      "uuid": 18292393
    },
    {
      "user": "rspadim",
      "count": 60,
      "uuid": 2468782
    },
    {
      "user": "gitrasheed",
      "count": 2,
      "uuid": 99349713
    }
  ],
  "_userbio": {
    "uuid": 18292393,
    "type": "user",
    "name": "OVVO-Financial",
    "description": "Operated and maintained by Fred Viole.  Each repository represents a current area of research interest.\r\n\r\nPapers available at:\r\nhttps://ssrn.com/author=1421356"
  },
  "_downloads": {
    "count": 1156,
    "source": "https://cranlogs.r-pkg.org/downloads/total/last-month/NNS"
  },
  "_mentions": 11,
  "_devurl": "https://github.com/ovvo-financial/nns",
  "_searchresults": 188,
  "_rbuild": "4.6.0",
  "_assets": [
    "extra/citation.cff",
    "extra/citation.html",
    "extra/citation.json",
    "extra/citation.txt",
    "extra/contents.json",
    "extra/NNS.html",
    "extra/readme.html",
    "extra/readme.md",
    "manual.pdf"
  ],
  "_homeurl": "https://github.com/ovvo-financial/nns",
  "_realowner": "ovvo-financial",
  "_cranurl": true,
  "_releases": [
    {
      "version": "0.1",
      "date": "2016-04-05"
    },
    {
      "version": "0.1.1",
      "date": "2016-04-06"
    },
    {
      "version": "0.1.3",
      "date": "2016-04-21"
    },
    {
      "version": "0.1.6",
      "date": "2016-05-11"
    },
    {
      "version": "0.1.9",
      "date": "2016-05-29"
    },
    {
      "version": "0.1.9.2",
      "date": "2016-06-14"
    },
    {
      "version": "0.1.9.4",
      "date": "2016-07-30"
    },
    {
      "version": "0.2.0",
      "date": "2016-08-18"
    },
    {
      "version": "0.2.1",
      "date": "2016-09-13"
    },
    {
      "version": "0.2.2",
      "date": "2016-09-29"
    },
    {
      "version": "0.2.3",
      "date": "2016-10-21"
    },
    {
      "version": "0.2.4",
      "date": "2016-11-28"
    },
    {
      "version": "0.2.5",
      "date": "2017-01-10"
    },
    {
      "version": "0.2.6",
      "date": "2017-02-12"
    },
    {
      "version": "0.3.0",
      "date": "2017-03-10"
    },
    {
      "version": "0.3.0.1",
      "date": "2017-03-11"
    },
    {
      "version": "0.3.1",
      "date": "2017-03-31"
    },
    {
      "version": "0.3.2",
      "date": "2017-05-01"
    },
    {
      "version": "0.3.3",
      "date": "2017-06-02"
    },
    {
      "version": "0.3.4",
      "date": "2017-06-27"
    },
    {
      "version": "0.3.5",
      "date": "2017-07-23"
    },
    {
      "version": "0.3.6",
      "date": "2017-08-15"
    },
    {
      "version": "0.3.7",
      "date": "2017-09-30"
    },
    {
      "version": "0.3.8",
      "date": "2017-11-13"
    },
    {
      "version": "0.3.8.1",
      "date": "2017-12-08"
    },
    {
      "version": "0.3.8.2",
      "date": "2018-01-08"
    },
    {
      "version": "0.3.8.3",
      "date": "2018-02-16"
    },
    {
      "version": "0.3.8.4",
      "date": "2018-03-17"
    },
    {
      "version": "0.3.8.6",
      "date": "2018-04-16"
    },
    {
      "version": "0.3.8.7",
      "date": "2018-05-15"
    },
    {
      "version": "0.3.8.8",
      "date": "2019-03-05"
    },
    {
      "version": "0.3.9",
      "date": "2019-04-15"
    },
    {
      "version": "0.4.0",
      "date": "2019-05-14"
    },
    {
      "version": "0.4.1",
      "date": "2019-06-11"
    },
    {
      "version": "0.4.2",
      "date": "2019-06-11"
    },
    {
      "version": "0.4.3",
      "date": "2019-07-19"
    },
    {
      "version": "0.4.4",
      "date": "2019-08-08"
    },
    {
      "version": "0.4.5",
      "date": "2019-09-09"
    },
    {
      "version": "0.4.6",
      "date": "2019-10-07"
    },
    {
      "version": "0.4.7",
      "date": "2019-11-19"
    },
    {
      "version": "0.4.7.1",
      "date": "2019-11-21"
    },
    {
      "version": "0.4.8",
      "date": "2020-01-08"
    },
    {
      "version": "0.4.9",
      "date": "2020-02-13"
    },
    {
      "version": "0.5.0",
      "date": "2020-03-17"
    },
    {
      "version": "0.5.1",
      "date": "2020-04-15"
    },
    {
      "version": "0.5.2",
      "date": "2020-05-17"
    },
    {
      "version": "0.5.2.1",
      "date": "2020-05-19"
    },
    {
      "version": "0.5.3",
      "date": "2020-06-19"
    },
    {
      "version": "0.5.4",
      "date": "2020-06-29"
    },
    {
      "version": "0.5.4.1",
      "date": "2020-07-01"
    },
    {
      "version": "0.5.4.2",
      "date": "2020-07-01"
    },
    {
      "version": "0.5.4.3",
      "date": "2020-08-01"
    },
    {
      "version": "0.5.5",
      "date": "2020-09-02"
    },
    {
      "version": "0.5.6",
      "date": "2020-12-03"
    },
    {
      "version": "0.5.7",
      "date": "2021-01-05"
    },
    {
      "version": "0.6",
      "date": "2021-02-04"
    },
    {
      "version": "0.6.1",
      "date": "2021-03-15"
    },
    {
      "version": "0.6.2",
      "date": "2021-03-15"
    },
    {
      "version": "0.6.3.1",
      "date": "2021-04-20"
    },
    {
      "version": "0.6.3.2",
      "date": "2021-04-21"
    },
    {
      "version": "0.7.0",
      "date": "2021-05-25"
    },
    {
      "version": "0.7.0.1",
      "date": "2021-05-27"
    },
    {
      "version": "0.7.1",
      "date": "2021-06-26"
    },
    {
      "version": "0.7.2",
      "date": "2021-08-06"
    },
    {
      "version": "0.8.0",
      "date": "2021-09-13"
    },
    {
      "version": "0.8.1",
      "date": "2021-09-20"
    },
    {
      "version": "0.8.2",
      "date": "2021-09-27"
    },
    {
      "version": "0.8.3",
      "date": "2021-11-23"
    },
    {
      "version": "0.8.4",
      "date": "2022-01-12"
    },
    {
      "version": "0.8.4.1",
      "date": "2022-01-13"
    },
    {
      "version": "0.8.5",
      "date": "2022-03-08"
    },
    {
      "version": "0.8.61",
      "date": "2022-04-04"
    },
    {
      "version": "0.8.70",
      "date": "2022-04-24"
    },
    {
      "version": "0.9.0",
      "date": "2022-08-06"
    },
    {
      "version": "0.9.1",
      "date": "2022-08-22"
    },
    {
      "version": "0.9.2",
      "date": "2022-09-23"
    },
    {
      "version": "0.9.2.1",
      "date": "2022-09-29"
    },
    {
      "version": "0.9.3",
      "date": "2022-11-03"
    },
    {
      "version": "0.9.4",
      "date": "2022-12-01"
    },
    {
      "version": "0.9.5",
      "date": "2023-01-08"
    },
    {
      "version": "0.9.6",
      "date": "2023-03-08"
    },
    {
      "version": "0.9.6.1",
      "date": "2023-03-08"
    },
    {
      "version": "0.9.7",
      "date": "2023-04-11"
    },
    {
      "version": "0.9.8",
      "date": "2023-05-17"
    },
    {
      "version": "0.9.9",
      "date": "2023-05-19"
    },
    {
      "version": "0.9.9.1",
      "date": "2023-06-15"
    },
    {
      "version": "10.0",
      "date": "2023-07-15"
    },
    {
      "version": "10.1",
      "date": "2023-08-26"
    },
    {
      "version": "10.2",
      "date": "2023-10-03"
    },
    {
      "version": "10.3",
      "date": "2023-11-10"
    },
    {
      "version": "10.4",
      "date": "2023-11-27"
    },
    {
      "version": "10.5",
      "date": "2024-01-10"
    },
    {
      "version": "10.6",
      "date": "2024-02-20"
    },
    {
      "version": "10.7",
      "date": "2024-03-07"
    },
    {
      "version": "10.8",
      "date": "2024-04-19"
    },
    {
      "version": "10.8.1",
      "date": "2024-05-11"
    },
    {
      "version": "10.8.2",
      "date": "2024-05-12"
    },
    {
      "version": "10.9",
      "date": "2024-08-19"
    },
    {
      "version": "10.9.1",
      "date": "2024-08-26"
    },
    {
      "version": "10.9.2",
      "date": "2024-09-06"
    },
    {
      "version": "10.9.3",
      "date": "2024-10-14"
    },
    {
      "version": "10.9.4",
      "date": "2024-12-02"
    },
    {
      "version": "10.9.5",
      "date": "2024-12-16"
    },
    {
      "version": "10.9.6",
      "date": "2024-12-17"
    },
    {
      "version": "11.0",
      "date": "2025-01-10"
    },
    {
      "version": "11.1",
      "date": "2025-02-17"
    },
    {
      "version": "11.2",
      "date": "2025-03-25"
    },
    {
      "version": "11.3",
      "date": "2025-04-28"
    },
    {
      "version": "11.4",
      "date": "2025-07-08"
    },
    {
      "version": "11.4.1",
      "date": "2025-07-15"
    },
    {
      "version": "11.5",
      "date": "2025-08-20"
    },
    {
      "version": "11.6",
      "date": "2025-09-26"
    },
    {
      "version": "11.6.1",
      "date": "2025-10-03"
    },
    {
      "version": "11.6.2",
      "date": "2025-10-04"
    },
    {
      "version": "11.6.3",
      "date": "2025-11-28"
    },
    {
      "version": "11.6.4",
      "date": "2026-01-10"
    },
    {
      "version": "11.6.5",
      "date": "2026-03-11"
    },
    {
      "version": "12.0",
      "date": "2026-04-10"
    },
    {
      "version": "12.1",
      "date": "2026-06-05"
    }
  ],
  "_exports": [
    "Co.LPM",
    "Co.LPM_nD",
    "Co.UPM",
    "Co.UPM_nD",
    "D.LPM",
    "D.UPM",
    "DPM_nD",
    "dy.d_",
    "dy.dx",
    "LPM",
    "LPM.ratio",
    "LPM.VaR",
    "NNS.ANOVA",
    "NNS.ARMA",
    "NNS.ARMA.optim",
    "NNS.boost",
    "NNS.caus",
    "NNS.CDF",
    "NNS.copula",
    "NNS.dep",
    "NNS.diff",
    "NNS.distance",
    "NNS.FSD",
    "NNS.FSD.uni",
    "NNS.gravity",
    "NNS.MC",
    "NNS.meboot",
    "NNS.mode",
    "NNS.moments",
    "NNS.norm",
    "NNS.part",
    "NNS.reg",
    "NNS.rescale",
    "NNS.SD.cluster",
    "NNS.SD.efficient.set",
    "NNS.seas",
    "NNS.SS",
    "NNS.SSD",
    "NNS.SSD.uni",
    "NNS.stack",
    "NNS.TSD",
    "NNS.TSD.uni",
    "NNS.VAR",
    "PM.matrix",
    "UPM",
    "UPM.ratio",
    "UPM.VaR"
  ],
  "_help": [
    {
      "page": "Co.LPM",
      "title": "Co‑Lower Partial Moment",
      "topics": [
        "Co.LPM"
      ]
    },
    {
      "page": "Co.LPM_nD",
      "title": "Co‑Lower Partial Moment nD",
      "topics": [
        "Co.LPM_nD"
      ]
    },
    {
      "page": "Co.UPM",
      "title": "Co‑Upper Partial Moment",
      "topics": [
        "Co.UPM"
      ]
    },
    {
      "page": "Co.UPM_nD",
      "title": "Co‑Upper Partial Moment nD",
      "topics": [
        "Co.UPM_nD"
      ]
    },
    {
      "page": "D.LPM",
      "title": "Divergent‑Lower Partial Moment",
      "topics": [
        "D.LPM"
      ]
    },
    {
      "page": "D.UPM",
      "title": "Divergent‑Upper Partial Moment",
      "topics": [
        "D.UPM"
      ]
    },
    {
      "page": "DPM_nD",
      "title": "Divergent Partial Moment nD",
      "topics": [
        "DPM_nD"
      ]
    },
    {
      "page": "dy.d_",
      "title": "Partial Derivative dy/d_[wrt]",
      "topics": [
        "dy.d_"
      ]
    },
    {
      "page": "dy.dx",
      "title": "Partial Derivative dy/dx",
      "topics": [
        "dy.dx"
      ]
    },
    {
      "page": "LPM",
      "title": "Lower Partial Moment",
      "topics": [
        "LPM"
      ]
    },
    {
      "page": "LPM.ratio",
      "title": "Lower Partial Moment Ratio",
      "topics": [
        "LPM.ratio"
      ]
    },
    {
      "page": "LPM.VaR",
      "title": "LPM VaR",
      "topics": [
        "LPM.VaR"
      ]
    },
    {
      "page": "NNS_bin",
      "title": "Fast binning of numeric vector into equidistant bins",
      "topics": [
        "NNS_bin"
      ]
    },
    {
      "page": "NNS.ANOVA",
      "title": "NNS ANOVA: Nonparametric Analysis of Variance",
      "topics": [
        "NNS.ANOVA"
      ]
    },
    {
      "page": "NNS.ARMA",
      "title": "NNS ARMA",
      "topics": [
        "NNS.ARMA"
      ]
    },
    {
      "page": "NNS.ARMA.optim",
      "title": "NNS ARMA Optimizer",
      "topics": [
        "NNS.ARMA.optim"
      ]
    },
    {
      "page": "NNS.boost",
      "title": "NNS Boost",
      "topics": [
        "NNS.boost"
      ]
    },
    {
      "page": "NNS.caus",
      "title": "NNS Causation",
      "topics": [
        "NNS.caus"
      ]
    },
    {
      "page": "NNS.CDF",
      "title": "NNS CDF",
      "topics": [
        "NNS.CDF"
      ]
    },
    {
      "page": "NNS.copula",
      "title": "NNS Co-Partial Moments Higher Dimension Dependence",
      "topics": [
        "NNS.copula"
      ]
    },
    {
      "page": "NNS.dep",
      "title": "NNS Dependence",
      "topics": [
        "NNS.dep"
      ]
    },
    {
      "page": "NNS.diff",
      "title": "NNS Numerical Differentiation",
      "topics": [
        "NNS.diff"
      ]
    },
    {
      "page": "NNS.distance",
      "title": "NNS Distance",
      "topics": [
        "NNS.distance"
      ]
    },
    {
      "page": "NNS.FSD",
      "title": "NNS FSD Test",
      "topics": [
        "NNS.FSD"
      ]
    },
    {
      "page": "NNS.FSD.uni",
      "title": "NNS FSD Test uni-directional",
      "topics": [
        "NNS.FSD.uni"
      ]
    },
    {
      "page": "NNS.gravity",
      "title": "NNS gravity",
      "topics": [
        "NNS.gravity"
      ]
    },
    {
      "page": "NNS.MC",
      "title": "NNS Monte Carlo Sampling",
      "topics": [
        "NNS.MC"
      ]
    },
    {
      "page": "NNS.meboot",
      "title": "NNS meboot",
      "topics": [
        "NNS.meboot"
      ]
    },
    {
      "page": "NNS.mode",
      "title": "NNS mode",
      "topics": [
        "NNS.mode"
      ]
    },
    {
      "page": "NNS.moments",
      "title": "NNS moments",
      "topics": [
        "NNS.moments"
      ]
    },
    {
      "page": "NNS.norm",
      "title": "NNS Normalization",
      "topics": [
        "NNS.norm"
      ]
    },
    {
      "page": "NNS.part",
      "title": "NNS Partition Map",
      "topics": [
        "NNS.part"
      ]
    },
    {
      "page": "NNS.reg",
      "title": "NNS Regression",
      "topics": [
        "NNS.reg"
      ]
    },
    {
      "page": "NNS.rescale",
      "title": "NNS rescale",
      "topics": [
        "NNS.rescale"
      ]
    },
    {
      "page": "NNS.SD.cluster",
      "title": "NNS SD-based Clustering",
      "topics": [
        "NNS.SD.cluster"
      ]
    },
    {
      "page": "NNS.SD.efficient.set",
      "title": "NNS SD Efficient Set",
      "topics": [
        "NNS.SD.efficient.set"
      ]
    },
    {
      "page": "NNS.seas",
      "title": "NNS Seasonality Test",
      "topics": [
        "NNS.seas"
      ]
    },
    {
      "page": "NNS.SS",
      "title": "NNS Stochastic Superiority",
      "topics": [
        "NNS.SS"
      ]
    },
    {
      "page": "NNS.SSD",
      "title": "NNS SSD Test",
      "topics": [
        "NNS.SSD"
      ]
    },
    {
      "page": "NNS.SSD.uni",
      "title": "NNS SSD Test uni-directional",
      "topics": [
        "NNS.SSD.uni"
      ]
    },
    {
      "page": "NNS.stack",
      "title": "NNS Stack",
      "topics": [
        "NNS.stack"
      ]
    },
    {
      "page": "NNS.TSD",
      "title": "NNS TSD Test",
      "topics": [
        "NNS.TSD"
      ]
    },
    {
      "page": "NNS.TSD.uni",
      "title": "NNS TSD Test uni-directional",
      "topics": [
        "NNS.TSD.uni"
      ]
    },
    {
      "page": "NNS.VAR",
      "title": "NNS VAR",
      "topics": [
        "NNS.VAR"
      ]
    },
    {
      "page": "PM.matrix",
      "title": "Partial Moment Matrix",
      "topics": [
        "PM.matrix"
      ]
    },
    {
      "page": "UPM",
      "title": "Upper Partial Moment",
      "topics": [
        "UPM"
      ]
    },
    {
      "page": "UPM.ratio",
      "title": "Upper Partial Moment Ratio",
      "topics": [
        "UPM.ratio"
      ]
    },
    {
      "page": "UPM.VaR",
      "title": "UPM VaR",
      "topics": [
        "UPM.VaR"
      ]
    }
  ],
  "_readme": "https://github.com/ovvo-financial/nns/raw/HEAD/README.md",
  "_rundeps": [
    "base64enc",
    "bslib",
    "cachem",
    "cli",
    "codetools",
    "data.table",
    "digest",
    "doParallel",
    "evaluate",
    "fastmap",
    "fontawesome",
    "foreach",
    "fs",
    "highr",
    "htmltools",
    "htmlwidgets",
    "iterators",
    "jquerylib",
    "jsonlite",
    "knitr",
    "lattice",
    "lifecycle",
    "magrittr",
    "memoise",
    "mime",
    "R6",
    "rappdirs",
    "Rcpp",
    "RcppArmadillo",
    "RcppParallel",
    "Rfast",
    "rgl",
    "rlang",
    "rmarkdown",
    "sass",
    "tinytex",
    "xfun",
    "xts",
    "yaml",
    "zigg",
    "zoo"
  ],
  "_sysdeps": [
    {
      "shlib": "libstdc++",
      "package": "libstdc++6",
      "source": "gcc",
      "version": "14.2.0-4ubuntu2~24.04.1",
      "name": "c++",
      "homepage": "http://gcc.gnu.org/",
      "description": "GNU Standard C++ Library v3"
    }
  ],
  "_vignettes": [
    {
      "source": "NNSvignette_01_Overview.Rmd",
      "filename": "NNSvignette_01_Overview.html",
      "title": "Getting Started with NNS: Overview",
      "author": "Fred Viole",
      "engine": "knitr::rmarkdown",
      "headings": [
        "Orientation",
        "1. Foundations — Partial Moments & Variance Decomposition",
        "1.1 Why partial moments",
        "1.2 Core functions and headers",
        "1.3 Code: variance decomposition & CDF",
        "2. Descriptive & Distributional Tools",
        "2.1 Higher moments from partial moments",
        "2.2 Mode estimation (no bin‑or‑bandwidth angst)",
        "2.3 CDF tables via LPM ratios",
        "3. Dependence & Nonlinear Association",
        "3.1 Why move beyond Pearson (r)",
        "3.2 Code: nonlinear dependence",
        "3.3 Code: copula",
        "4. Normalization and Rescaling",
        "4.1 Normalization",
        "4.2 Risk‑neutral rescale (pricing context)",
        "5. Hypothesis Testing, ANOVA & Stochastic Superiority",
        "5.1 Concept",
        "5.2 Code: two‑sample & multi‑group",
        "5.3 Stochastic Superiority",
        "6. Regression, Boosting, Stacking & Causality",
        "6.1 Philosophy",
        "6.2 Code: classification via regression + ensembles",
        "6.3 Code: directional causality",
        "7. Time Series & Forecasting",
        "8. Simulation & Bootstrap & Risk‑Neutral Rescaling",
        "8.1 Maximum entropy bootstrap (shape‑preserving)",
        "8.2 Monte Carlo over the full correlation space",
        "9. Portfolio & Stochastic Dominance",
        "Appendix A — Measure‑theoretic sketch (why partial moments are rigorous)",
        "Appendix B — Quick Reference (Grouped by Topic)",
        "Overall Theory",
        "1. Partial Moments & Ratios",
        "2. Descriptive Statistics & Distributions",
        "3. Dependence & Association",
        "4. Normalization & Rescaling",
        "5. Hypothesis Testing",
        "6. Regression, Classification & Causality",
        "7. Differentiation & Slope Measures",
        "8. Time Series & Forecasting",
        "9. Simulation & Bootstrap",
        "10. Portfolio Analysis & Stochastic Dominance"
      ],
      "created": "2026-06-04 16:35:27",
      "modified": "2026-06-04 16:57:38",
      "commits": 2
    },
    {
      "source": "NNSvignette_02_Partial_Moments.Rmd",
      "filename": "NNSvignette_02_Partial_Moments.html",
      "title": "Getting Started with NNS: Partial Moments",
      "author": "Fred Viole",
      "engine": "knitr::rmarkdown",
      "headings": [
        "Partial Moments",
        "Mean",
        "Variance",
        "Standard Deviation",
        "First 4 Moments",
        "Statistical Mode of a Continuous Distribution",
        "Covariance",
        "Covariance Elements and Covariance Matrix",
        "Pearson Correlation",
        "CDFs (Discrete and Continuous)",
        "Numerical Integration",
        "Bayes' Theorem",
        "References"
      ],
      "created": "2026-06-04 16:35:27",
      "modified": "2026-06-04 16:35:27",
      "commits": 1
    },
    {
      "source": "NNSvignette_03_Correlation_and_Dependence.Rmd",
      "filename": "NNSvignette_03_Correlation_and_Dependence.html",
      "title": "Getting Started with NNS: Correlation and Dependence",
      "author": "Fred Viole",
      "engine": "knitr::rmarkdown",
      "headings": [
        "Correlation and Dependence",
        "Linear Equivalence",
        "Nonlinear Relationship",
        "Cyclic Relationship",
        "Asymmetrical Analysis",
        "Dependence",
        "p-values for NNS.dep()",
        "Multivariate Dependence NNS.copula()",
        "References"
      ],
      "created": "2026-06-04 16:35:27",
      "modified": "2026-06-04 16:35:27",
      "commits": 1
    },
    {
      "source": "NNSvignette_04_Normalization_and_Rescaling.Rmd",
      "filename": "NNSvignette_04_Normalization_and_Rescaling.html",
      "title": "Getting Started with NNS: Normalization and Rescaling",
      "author": "Fred Viole",
      "engine": "knitr::rmarkdown",
      "headings": [
        "Overview",
        "NNS.norm(): Normalize Multiple Variables",
        "Mathematical Structure",
        "Step 1: Compute Mean Vector",
        "Step 2: Construct Mean Ratio Matrix",
        "Step 3: Dependence Weight Matrix",
        "Step 4: Scaling Factors",
        "Linear Case Proof",
        "Nonlinear Case Interpretation",
        "[\\text{mean}(X_{\\cdot j}^{*})",
        "Examples",
        "Basic Multivariate Example",
        "Normalize list of unequal vector lengths",
        "Quantile Normalization Comparison",
        "Practical Applications",
        "NNS.rescale(): Distribution Rescaling",
        "1) Min-Max Scaling",
        "[x^",
        "Example",
        "2) Risk-Neutral Scaling",
        "Terminal Type",
        "Discounted Type",
        "Risk-Neutral Example",
        "Discounted Example",
        "Conceptual Summary",
        "NNS.norm()",
        "NNS.rescale()",
        "References"
      ],
      "created": "2026-06-04 16:35:27",
      "modified": "2026-06-04 16:35:27",
      "commits": 1
    },
    {
      "source": "NNSvignette_05_Sampling.Rmd",
      "filename": "NNSvignette_05_Sampling.html",
      "title": "Getting Started with NNS: Sampling and Simulation",
      "author": "Fred Viole",
      "engine": "knitr::rmarkdown",
      "headings": [
        "Sampling",
        "CDFs",
        "Empirical CDF",
        "Lower Partial Moment CDF (LPM.ratio)",
        "LPM.ratio degree > 0",
        "Generating PDFs with (LPM.VaR)",
        "Simulation",
        "Bootstrapping (NNS.meboot)",
        "target_drift Specification",
        "Simulating a Multivariate Dependence Structure",
        "Compare Multivariate Dependence Structures",
        "Alternative Using NNS.meboot",
        "References"
      ],
      "created": "2026-06-04 16:35:27",
      "modified": "2026-06-04 16:35:27",
      "commits": 1
    },
    {
      "source": "NNSvignette_06_Comparing_Distributions.Rmd",
      "filename": "NNSvignette_06_Comparing_Distributions.html",
      "title": "Getting Started with NNS: Comparing Distributions",
      "author": "Fred Viole",
      "engine": "knitr::rmarkdown",
      "headings": [
        "Comparing Distributions",
        "Test if Same Population",
        "Test if means are Equal",
        "Test if means are Unequal",
        "Medians",
        "Stochastic Superiority",
        "Stochastic Dominance",
        "Stochastic Dominant Efficient Sets",
        "Stochastic Dominant Clusters",
        "References"
      ],
      "created": "2026-06-04 16:35:27",
      "modified": "2026-06-04 16:35:27",
      "commits": 1
    },
    {
      "source": "NNSvignette_07_Clustering_and_Regression.Rmd",
      "filename": "NNSvignette_07_Clustering_and_Regression.html",
      "title": "Getting Started with NNS: Clustering and Regression",
      "author": "Fred Viole",
      "engine": "knitr::rmarkdown",
      "headings": [
        "Clustering and Regression",
        "NNS Partitioning NNS.part()",
        "X-only Partitioning",
        "Clusters Used in Regression",
        "NNS Regression NNS.reg()",
        "Univariate:",
        "Multivariate:",
        "Inter/Extrapolation",
        "NNS Dimension Reduction Regression",
        "Threshold",
        "Classification",
        "Cross-Validation NNS.stack()",
        "Increasing Dimensions",
        "Smoothing Option",
        "Imputation",
        "Univariate Imputation",
        "Multivariate Imputation",
        "A Note on Uncertainty Propagation",
        "References"
      ],
      "created": "2026-06-04 16:35:27",
      "modified": "2026-06-04 16:35:27",
      "commits": 1
    },
    {
      "source": "NNSvignette_08_Classification.Rmd",
      "filename": "NNSvignette_08_Classification.html",
      "title": "Getting Started with NNS: Classification",
      "author": "Fred Viole",
      "engine": "knitr::rmarkdown",
      "headings": [
        "Classification",
        "Splits vs. Partitions",
        "NNS Partitions",
        "NNS.boost()",
        "Cross-Validation Classification Using NNS.stack()",
        "Brief Notes on Other Parameters",
        "References"
      ],
      "created": "2026-06-04 16:35:27",
      "modified": "2026-06-04 16:35:27",
      "commits": 1
    },
    {
      "source": "NNSvignette_09_Forecasting.Rmd",
      "filename": "NNSvignette_09_Forecasting.html",
      "title": "Getting Started with NNS: Forecasting",
      "author": "Fred Viole",
      "engine": "knitr::rmarkdown",
      "headings": [
        "Forecasting",
        "Linear Regression",
        "Nonlinear Regression",
        "Cross-Validation",
        "Cross-Validating All Combinations of seasonal.factor",
        "Extension of Estimates",
        "Brief Notes on Other Parameters",
        "Multivariate Time Series Forecasting",
        "References"
      ],
      "created": "2026-06-04 16:35:27",
      "modified": "2026-06-04 16:35:27",
      "commits": 1
    }
  ],
  "_score": 11.814506117209719,
  "_indexed": true,
  "_nocasepkg": "nns",
  "_universes": [
    "ovvo-financial"
  ],
  "_previous": "12.1",
  "_binaries": [
    {
      "r": "4.7.0",
      "os": "linux",
      "version": "12.2",
      "date": "2026-06-08T14:57:48.000Z",
      "distro": "noble",
      "arch": "aarch64",
      "commit": "0578c17dbbcb9786fb53719c40c7adcab038dd73",
      "fileid": "82c436eaf3b8dfca4738b653d1f11a80c58bf9e5210c52b05eb115fcd60de524",
      "status": "success",
      "check": "WARNING",
      "buildurl": "https://github.com/r-universe/ovvo-financial/actions/runs/27145904463"
    },
    {
      "r": "4.7.0",
      "os": "linux",
      "version": "12.2",
      "date": "2026-06-08T14:58:11.000Z",
      "distro": "noble",
      "arch": "x86_64",
      "commit": "0578c17dbbcb9786fb53719c40c7adcab038dd73",
      "fileid": "e24a7013a68cb6d7c14d06e5a4a20b4f4bc2a0f27b8b33a5ea6cdf5b548c8df1",
      "status": "success",
      "check": "WARNING",
      "buildurl": "https://github.com/r-universe/ovvo-financial/actions/runs/27145904463"
    },
    {
      "r": "4.6.0",
      "os": "linux",
      "version": "12.2",
      "date": "2026-06-08T14:57:50.000Z",
      "distro": "noble",
      "arch": "aarch64",
      "commit": "0578c17dbbcb9786fb53719c40c7adcab038dd73",
      "fileid": "00be76f01d2ea4af682cb44eef01fabf9f377ab710131be169ff28ea595fea63",
      "status": "success",
      "check": "WARNING",
      "buildurl": "https://github.com/r-universe/ovvo-financial/actions/runs/27145904463"
    },
    {
      "r": "4.6.0",
      "os": "linux",
      "version": "12.2",
      "date": "2026-06-08T14:57:22.000Z",
      "distro": "noble",
      "arch": "x86_64",
      "commit": "0578c17dbbcb9786fb53719c40c7adcab038dd73",
      "fileid": "2a4c42f02bb8657fad1d36184c08d0b810ea7b41fdc970a7933d27b0a30705a5",
      "status": "success",
      "check": "WARNING",
      "buildurl": "https://github.com/r-universe/ovvo-financial/actions/runs/27145904463"
    },
    {
      "r": "4.5.3",
      "os": "mac",
      "version": "12.2",
      "date": "2026-06-08T15:00:57.000Z",
      "arch": "aarch64",
      "commit": "0578c17dbbcb9786fb53719c40c7adcab038dd73",
      "fileid": "c6958f4f7c67ed24f91d008b21f49bdcbb5669340f5d15b119936822b2d49439",
      "status": "success",
      "check": "WARNING",
      "buildurl": "https://github.com/r-universe/ovvo-financial/actions/runs/27145904463"
    },
    {
      "r": "4.5.3",
      "os": "mac",
      "version": "12.2",
      "date": "2026-06-08T14:59:05.000Z",
      "arch": "x86_64",
      "commit": "0578c17dbbcb9786fb53719c40c7adcab038dd73",
      "fileid": "6947f29bf54e5f39477563fdac4bd046f6b03cd9211101183c23ae662c50582f",
      "status": "success",
      "check": "WARNING",
      "buildurl": "https://github.com/r-universe/ovvo-financial/actions/runs/27145904463"
    },
    {
      "r": "4.6.0",
      "os": "mac",
      "version": "12.2",
      "date": "2026-06-08T14:58:00.000Z",
      "arch": "aarch64",
      "commit": "0578c17dbbcb9786fb53719c40c7adcab038dd73",
      "fileid": "ba863ca28cd8ba0add402a549cce740b85588f25090797743164baa8b4202717",
      "status": "success",
      "check": "WARNING",
      "buildurl": "https://github.com/r-universe/ovvo-financial/actions/runs/27145904463"
    },
    {
      "r": "4.6.0",
      "os": "mac",
      "version": "12.2",
      "date": "2026-06-08T15:00:08.000Z",
      "arch": "x86_64",
      "commit": "0578c17dbbcb9786fb53719c40c7adcab038dd73",
      "fileid": "5f4252d9efd85e5e93082f3a38c08acb65a74b0c9f5380409411d5e0a1de31cb",
      "status": "success",
      "check": "WARNING",
      "buildurl": "https://github.com/r-universe/ovvo-financial/actions/runs/27145904463"
    },
    {
      "r": "4.6.0",
      "os": "wasm",
      "version": "12.2",
      "date": "2026-06-08T14:57:24.000Z",
      "arch": "emscripten",
      "commit": "0578c17dbbcb9786fb53719c40c7adcab038dd73",
      "fileid": "4006df07af9b2094f389a0f1003f1968aefa654ce234b1847d1dc825572a925e",
      "status": "success",
      "buildurl": "https://github.com/r-universe/ovvo-financial/actions/runs/27145904463"
    },
    {
      "r": "4.7.0",
      "os": "win",
      "version": "12.2",
      "date": "2026-06-08T14:56:33.000Z",
      "arch": "x86_64",
      "commit": "0578c17dbbcb9786fb53719c40c7adcab038dd73",
      "fileid": "a78ba95f84b43132793a47015289360fac7d52de7230b2ab2b50b76281d6bad8",
      "status": "success",
      "check": "WARNING",
      "buildurl": "https://github.com/r-universe/ovvo-financial/actions/runs/27145904463"
    },
    {
      "r": "4.5.3",
      "os": "win",
      "version": "12.2",
      "date": "2026-06-08T14:56:12.000Z",
      "arch": "x86_64",
      "commit": "0578c17dbbcb9786fb53719c40c7adcab038dd73",
      "fileid": "d41bbe5ee7ba146dd2c32a7f7286e63712da3dc34541d84a688652d68b04c51a",
      "status": "success",
      "check": "WARNING",
      "buildurl": "https://github.com/r-universe/ovvo-financial/actions/runs/27145904463"
    },
    {
      "r": "4.6.0",
      "os": "win",
      "version": "12.2",
      "date": "2026-06-08T14:56:15.000Z",
      "arch": "x86_64",
      "commit": "0578c17dbbcb9786fb53719c40c7adcab038dd73",
      "fileid": "c0c316d84765f6bea7d00ac1f3df4c8d6c50177b96485ceeb567f8a2d7b80941",
      "status": "success",
      "check": "WARNING",
      "buildurl": "https://github.com/r-universe/ovvo-financial/actions/runs/27145904463"
    }
  ]
}