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  "Title": "Fitting Point Process Models via the Palm Likelihood",
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  "Description": "Functions to fit point process models using the Palm\nlikelihood. First proposed by Tanaka, Ogata, and Stoyan (2008)\n<DOI:10.1002/bimj.200610339>, maximisation of the Palm\nlikelihood can provide computationally efficient parameter\nestimation for point process models in situations where the\nfull likelihood is intractable. This package is chiefly focused\non Neyman-Scott point processes, but can also fit the void\nprocesses proposed by Jones-Todd et al. (2019)\n<DOI:10.1002/sim.8046>. The development of this package was\nmotivated by the analysis of capture-recapture surveys on which\nindividuals cannot be identified---the data from which can\nconceptually be seen as a clustered point process (Stevenson,\nBorchers, and Fewster, 2019 <DOI:10.1111/biom.12983>). As such,\nsome of the functions in this package are specifically for the\nestimation of cetacean density from two-camera aerial surveys.",
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      "fileid": "https://r2.ropensci.org/5e32e92dfc3ba9418132c8162a5a203ef53821031459d87a1525062ec3ff32d5",
      "status": "success",
      "check": "OK",
      "buildurl": "https://github.com/r-universe/b-steve/actions/runs/39111791638"
    }
  ]
}