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  "Title": "Species Abundance Distributions with Independent-Species\nAssumption",
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  "Author": "Rampal S. Etienne & Bart Haegeman",
  "Maintainer": "Rampal S. Etienne <r.s.etienne@rug.nl>",
  "Description": "Computes the probability of a set of species abundances of\na single or multiple samples of individuals with one or more\nguilds under a mainland-island model. One must specify the\nmainland (metacommunity) model and the island (local) community\nmodel. It assumes that species fluctuate independently. The\npackage also contains functions to simulate under this model.\nSee Haegeman, B. & R.S. Etienne (2017). A general sampling\nformula for community structure data. Methods in Ecology &\nEvolution 8: 1506-1519 <doi:10.1111/2041-210X.12807>.",
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  "Repository": "https://rsetienne.r-universe.dev",
  "Date/Publication": "2020-08-18 08:50:39 UTC",
  "RemoteUrl": "https://github.com/rsetienne/sadisa",
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      "date": "2019-04-08"
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    "integral_peak",
    "SADISA_loglik",
    "SADISA_ML",
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    "SADISA_test"
  ],
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      ],
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    {
      "page": "convert_fa2sf",
      "title": "Converts different formats to represent multiple sample data",
      "topics": [
        "convert_fa2sf"
      ]
    },
    {
      "page": "datasets",
      "title": "Data sets of various tropical forest communities",
      "topics": [
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      ]
    },
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      "title": "Maximum likelihood estimates and corresponding likelihood values for various fits to various tropical forest communities",
      "topics": [
        "fitresults"
      ]
    },
    {
      "page": "integral_peak",
      "title": "Computes integral of a very peaked function",
      "topics": [
        "integral_peak"
      ]
    },
    {
      "page": "SADISA_loglik",
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      "topics": [
        "SADISA_loglik"
      ]
    },
    {
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      "topics": [
        "SADISA_ML"
      ]
    },
    {
      "page": "SADISA_sim",
      "title": "Simulates species abundance data",
      "topics": [
        "SADISA_sim"
      ]
    },
    {
      "page": "SADISA_test",
      "title": "Tests SADISA for data sets included in the paper by Haegeman & Etienne",
      "topics": [
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      ]
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