{ "_id": "6a115083acfb0bcc41cea400", "Package": "spOccupancy", "Type": "Package", "Title": "Single-Species, Multi-Species, and Integrated Spatial Occupancy\nModels", "Version": "0.8.1", "Authors@R": "c(person(\"Jeffrey\", \"Doser\", role=c(\"aut\", \"cre\"), email=\"jwdoser@ncsu.edu\"), person(\"Andrew\", \"Finley\", role = c(\"aut\")), person(\"Marc\", \"Kery\", role = c('ctb')))", "Author": "Jeffrey Doser [aut, cre], Andrew Finley [aut], Marc Kery [ctb]", "Maintainer": "Jeffrey Doser ", "Description": "Fits single-species, multi-species, and integrated\nnon-spatial and spatial occupancy models using Markov Chain\nMonte Carlo (MCMC). Models are fit using Polya-Gamma data\naugmentation detailed in Polson, Scott, and Windle (2013)\n. Spatial models are fit\nusing either Gaussian processes or Nearest Neighbor Gaussian\nProcesses (NNGP) for large spatial datasets. Details on NNGP\nmodels are given in Datta, Banerjee, Finley, and Gelfand (2016)\n and Finley, Datta, and\nBanerjee (2022) . Provides\nfunctionality for data integration of multiple single-species\noccupancy data sets using a joint likelihood framework. Details\non data integration are given in Miller, Pacifici, Sanderlin,\nand Reich (2019) . Details on\nsingle-species and multi-species models are found in MacKenzie,\nNichols, Lachman, Droege, Royle, and Langtimm (2002)\n and\nDorazio and Royle ,\nrespectively.", "License": "GPL (>= 3)", "Encoding": "UTF-8", "LazyData": "true", "RoxygenNote": "7.1.1", "URL": "https://www.doserlab.com/files/spoccupancy-web,\nhttps://groups.google.com/g/spocc-spabund-users,\nhttps://github.com/biodiverse/spOccupancy", "BugReports": "https://github.com/biodiverse/spOccupancy/issues", "NeedsCompilation": "yes", "Config/pak/sysreqs": "cmake make", "Repository": "https://ecoverser.r-universe.dev", "Date/Publication": "2025-07-18 15:57:39 UTC", "RemoteUrl": "https://github.com/ecoverser/spoccupancy", "RemoteRef": "HEAD", "RemoteSha": "d2942b91e33d9bb073a8aa8ca86db22f4fbf729e", "Packaged": { "Date": "2026-05-23 06:50:07 UTC", "User": "root" }, "MD5sum": "66faca32b3f649ed8c47d57c0603129f", "_user": "ecoverser", "_type": "src", "_file": "spOccupancy_0.8.1.tar.gz", "_fileid": 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"topics": [ "plot.sfMsPGOcc", "print.sfMsPGOcc", "summary.sfMsPGOcc" ] }, { "page": "summary.spIntPGOcc", "title": "Methods for spIntPGOcc Object", "topics": [ "plot.spIntPGOcc", "print.spIntPGOcc", "summary.spIntPGOcc" ] }, { "page": "summary.spMsPGOcc", "title": "Methods for spMsPGOcc Object", "topics": [ "plot.spMsPGOcc", "print.spMsPGOcc", "summary.spMsPGOcc" ] }, { "page": "summary.spPGOcc", "title": "Methods for spPGOcc Object", "topics": [ "plot.spPGOcc", "print.spPGOcc", "summary.spPGOcc" ] }, { "page": "summary.stIntPGOcc", "title": "Methods for stIntPGOcc Object", "topics": [ "plot.stIntPGOcc", "print.stIntPGOcc", "summary.stIntPGOcc" ] }, { "page": "summary.stMsPGOcc", "title": "Methods for stMsPGOcc Object", "topics": [ "plot.stMsPGOcc", "print.stMsPGOcc", "summary.stMsPGOcc" ] }, { "page": "summary.stPGOcc", "title": "Methods for stPGOcc Object", "topics": [ "plot.stPGOcc", "print.stPGOcc", "summary.stPGOcc" ] }, { "page": "summary.svcMsPGOcc", "title": "Methods for svcMsPGOcc Object", "topics": [ "plot.svcMsPGOcc", "print.svcMsPGOcc", "summary.svcMsPGOcc" ] }, { "page": "summary.svcPGBinom", "title": "Methods for svcPGBinom Object", "topics": [ "plot.svcPGBinom", "print.svcPGBinom", "summary.svcPGBinom" ] }, { "page": "summary.svcPGOcc", "title": "Methods for svcPGOcc Object", "topics": [ "plot.svcPGOcc", "print.svcPGOcc", "summary.svcPGOcc" ] }, { "page": "summary.svcTIntPGOcc", "title": "Methods for svcTIntPGOcc Object", "topics": [ "plot.svcTIntPGOcc", "print.svcTIntPGOcc", "summary.svcTIntPGOcc" ] }, { "page": "summary.svcTMsPGOcc", "title": "Methods for svcTMsPGOcc Object", "topics": [ "plot.svcTMsPGOcc", "print.svcTMsPGOcc", "summary.svcTMsPGOcc" ] }, { "page": "summary.svcTPGBinom", "title": "Methods for svcTPGBinom Object", "topics": [ "plot.svcTPGBinom", "print.svcTPGBinom", "summary.svcTPGBinom" ] }, { "page": "summary.svcTPGOcc", "title": "Methods for svcTPGOcc Object", "topics": [ "plot.svcTPGOcc", "print.svcTPGOcc", "summary.svcTPGOcc" ] }, { "page": "summary.tIntPGOcc", "title": "Methods for tIntPGOcc Object", "topics": [ "plot.tIntPGOcc", "print.tIntPGOcc", "summary.tIntPGOcc" ] }, { "page": "summary.tMsPGOcc", "title": "Methods for tMsPGOcc Object", "topics": [ "plot.tMsPGOcc", "print.tMsPGOcc", "summary.tMsPGOcc" ] }, { "page": "summary.tPGOcc", "title": "Methods for tPGOcc Object", "topics": [ "plot.tPGOcc", "print.tPGOcc", "summary.tPGOcc" ] }, { "page": "svcMsPGOcc", "title": "Function for Fitting Multi-Species Spatially-Varying Coefficient Occupancy Models", "topics": [ "svcMsPGOcc" ] }, { "page": "svcPGBinom", "title": "Function for Fitting Single-Species Spatially-Varying Coefficient Binomial Models Using Polya-Gamma Latent Variables", "topics": [ "svcPGBinom" ] }, { "page": "svcPGOcc", "title": "Function for Fitting Single-Species Spatially-Varying Coefficient Occupancy Models Using Polya-Gamma Latent Variables", "topics": [ "svcPGOcc" ] }, { "page": "svcTIntPGOcc", "title": "Function 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