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  "Package": "sparsesurv",
  "Title": "Forecasting and Early Outbreak Detection for Sparse Count Data",
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  "Authors@R": "c(\nperson(\"Alexandros\", \"Angelakis\",\nemail = \"alexandros.angelakis@swisstph.ch\",\nrole = c(\"aut\", \"cre\")),\nperson(\"Bryan\",\"Nyawanda\",role = \"aut\"),\nperson(\"Penelope\",\"Vounatsou\",role = \"aut\")\n)",
  "Description": "Functions for fitting, forecasting, and early detection of\noutbreaks in sparse surveillance count time series. Supports\nnegative binomial (NB), self-exciting NB, generalise\nautoregressive moving average (GARMA) NB , zero-inflated NB\n(ZINB), self-exciting ZINB, generalise autoregressive moving\naverage ZINB, and hurdle formulations. Climatic and\nenvironmental covariates can be included in the regression\ncomponent and/or the zero-modified components. Includes\noutbreak-detection algorithms for NB, ZINB, and hurdle models,\nwith utilities for prediction and diagnostics.",
  "License": "GPL (>= 3)",
  "Encoding": "UTF-8",
  "Config/testthat/edition": "3",
  "Roxygen": "list(markdown = TRUE)",
  "SystemRequirements": "JAGS (>= 4.x)",
  "URL": "https://github.com/alexangelakis-ang/sparsesurv",
  "BugReports": "https://github.com/alexangelakis-ang/sparsesurv/issues",
  "RoxygenNote": "7.3.2",
  "Config/pak/sysreqs": "jags libicu-dev",
  "Repository": "https://alexangelakis-ang.r-universe.dev",
  "Date/Publication": "2025-09-04 08:35:29 UTC",
  "RemoteUrl": "https://github.com/alexangelakis-ang/sparsesurv",
  "RemoteRef": "HEAD",
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  "Packaged": {
    "Date": "2026-05-11 07:35:23 UTC",
    "User": "root"
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  "Author": "Alexandros Angelakis [aut, cre],\nBryan Nyawanda [aut],\nPenelope Vounatsou [aut]",
  "Maintainer": "Alexandros Angelakis <alexandros.angelakis@swisstph.ch>",
  "MD5sum": "5f8ec93ccf710c0fe2b3a9962fc1b69a",
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    "author": "Alexandros Angelakis <alexandros.angelakis@swisstph.ch>",
    "committer": "Alexandros Angelakis <alexandros.angelakis@swisstph.ch>",
    "message": "Answer to comments (CRAN)\n",
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      "title": "Fit Negative Binomial GARMA Model with Prediction",
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      "title": "Fit Negative Binomial Model with Arbitrary Covariates",
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      ]
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      "page": "outbreakHNB",
      "title": "Fit an outbreak detection Hurdle negative binomial outbreak model",
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    },
    {
      "page": "outbreakNB",
      "title": "Fit an outbreak detection negative binomial outbreak model",
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    },
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      "title": "Fit an outbreak detection zero‐inflated negative binomial outbreak model",
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    }
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