{
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  "Package": "NST",
  "Type": "Package",
  "Title": "Normalized Stochasticity Ratio",
  "Version": "3.1.10",
  "Date": "2022-6-3",
  "Author": "Daliang Ning",
  "Maintainer": "Daliang Ning <ningdaliang@ou.edu>",
  "Description": "To estimate ecological stochasticity in community\nassembly. Understanding the community assembly mechanisms\ncontrolling biodiversity patterns is a central issue in\necology. Although it is generally accepted that both\ndeterministic and stochastic processes play important roles in\ncommunity assembly, quantifying their relative importance is\nchallenging. The new index, normalized stochasticity ratio\n(NST), is to estimate ecological stochasticity, i.e. relative\nimportance of stochastic processes, in community assembly. With\nfunctions in this package, NST can be calculated based on\ndifferent similarity metrics and/or different null model\nalgorithms, as well as some previous indexes, e.g. previous\nStochasticity Ratio (ST), Standard Effect Size (SES), modified\nRaup-Crick metrics (RC). Functions for permutational test and\nbootstrapping analysis are also included. Previous ST is\npublished by Zhou et al (2014) <doi:10.1073/pnas.1324044111>.\nNST is modified from ST by considering two alternative\nsituations and normalizing the index to range from 0 to 1 (Ning\net al 2019) <doi:10.1073/pnas.1904623116>. A modified version,\nMST, is a special case of NST, used in some recent or upcoming\npublications, e.g. Liang et al (2020)\n<doi:10.1016/j.soilbio.2020.108023>. SES is calculated as\ndescribed in Kraft et al (2011) <doi:10.1126/science.1208584>.\nRC is calculated as reported by Chase et al (2011)\n<doi:10.1890/ES10-00117.1> and Stegen et al (2013)\n<doi:10.1038/ismej.2013.93>. Version 3 added NST based on\nphylogenetic beta diversity, used by Ning et al (2020)\n<doi:10.1038/s41467-020-18560-z>.",
  "License": "GPL-2",
  "URL": "https://github.com/DaliangNing/NST",
  "NeedsCompilation": "no",
  "Packaged": {
    "Date": "2026-05-16 05:53:35 UTC",
    "User": "root"
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  "Repository": "https://cran.r-universe.dev",
  "Date/Publication": "2022-06-05 15:00:09 UTC",
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    "author": "Daliang Ning <ningdaliang@ou.edu>",
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    "message": "version 3.1.10\n",
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      "title": "Test data B observed and null beta diversity",
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      "class": [
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    },
    {
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      "title": "Test dataset A",
      "object": "tda",
      "file": "tda.rda",
      "class": [
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      ],
      "fields": [],
      "table": false,
      "tojson": false
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  "_help": [
    {
      "page": "NST-package",
      "title": "Normalized Stochasticity Ratio",
      "topics": [
        "NST-package",
        "NST"
      ]
    },
    {
      "page": "ab.assign",
      "title": "Randomly draw individuals into species according to specified probabilities",
      "topics": [
        "ab.assign"
      ]
    },
    {
      "page": "beta.g",
      "title": "Various taxonomic beta diversity indexes",
      "topics": [
        "beta.g",
        "chaojaccard",
        "chaosorensen"
      ]
    },
    {
      "page": "beta.limit",
      "title": "Upper limit of different beta diversity (dissimilarity) indexes",
      "topics": [
        "beta.limit"
      ]
    },
    {
      "page": "beta.obs.rand",
      "title": "Test data B observed and null beta diversity",
      "topics": [
        "beta.obs.rand"
      ]
    },
    {
      "page": "bmntd.big",
      "title": "beta mean nearest taxon distance (betaMNTD) from big data",
      "topics": [
        "bmntd.big"
      ]
    },
    {
      "page": "cNST",
      "title": "Normalized Stochasticity Ratio based on customized metrics and null results",
      "topics": [
        "cNST"
      ]
    },
    {
      "page": "dist.3col",
      "title": "Transform distance matrix to 3-column matrix",
      "topics": [
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    },
    {
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      "title": "Check and ensure the consistency of IDs in different objects.",
      "topics": [
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      "title": "Bootstrapping test for ST and NST",
      "topics": [
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    {
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      "title": "Permutational multivariate ANOVA test for ST and NST",
      "topics": [
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      "title": "Options of null model algorithms",
      "topics": [
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      "topics": [
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    },
    {
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      "topics": [
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      ]
    },
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