{
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  "Package": "flocker",
  "Title": "Flexible Occupancy Estimation with Stan",
  "Version": "1.0-2",
  "Authors@R": "c(\nperson(\"Jacob B.\", \"Socolar\", , \"jacob.socolar@gmail.com\", role = c(\"aut\", \"cre\", \"cph\")),\nperson(\"Simon C.\", \"Mills\", role = \"aut\"),\nperson(\"Paul-Christian\", \"Bürkner\", role = \"ctb\")\n)",
  "Description": "Fit occupancy models in 'Stan' via 'brms'. The full\nvariety of 'brms' formula-based effects structures are\navailable to use in multiple classes of occupancy model,\nincluding single-season models, models with data augmentation\nfor never-observed species, dynamic (multiseason) models with\nexplicit colonization and extinction processes, and dynamic\nmodels with autologistic occupancy dynamics. Formulas can be\nspecified for all relevant distributional terms, including\ndetection and one or more of occupancy, colonization,\nextinction, and autologistic depending on the model type.\nSeveral important forms of model post-processing are provided.\nReferences: Bürkner (2017) <doi:10.18637/jss.v080.i01>;\nCarpenter et al. (2017) <doi:10.18637/jss.v076.i01>; Socolar &\nMills (2023) <doi:10.1101/2023.10.26.564080>.",
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  "URL": "https://github.com/jsocolar/flocker,\nhttps://jsocolar.github.io/flocker/",
  "BugReports": "https://github.com/jsocolar/flocker/issues",
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  "Date/Publication": "2026-04-30 02:27:13 UTC",
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      "title": "Posterior predictive distributions for modeled probabilities",
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      "title": "Fit an occupancy model",
      "topics": [
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    },
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    {
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      "title": "Generate stan data for an occupancy model",
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      "topics": [
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      "title": "LOO comparisons for flocker models.",
      "topics": [
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      ]
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    {
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      "title": "Compute loo for flocker_fit objects",
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      "topics": [
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    }
  ]
}