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  "Title": "Bayesian Hierarchical Modeling for Duration-Dependent GEV",
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  "Description": "The dgevbhm package is a software package written in R and\nStan that offers a Bayesian hierarchical regional framework to\nestimate the occurrence probability of extreme precipitation\nbased on small sample sizes, as sub-daily observations and\nhigh-resolution climate model simulations typically cover less\nthan 50 years. dgevbhm features Bayesian parameter estimation\nfor the duration-dependent Generalized Extreme Value\ndistribution, which requires annual maxima of precipitation\nacross different durations. By utilizing No U-turn sampling via\nrstan, models sample posterior samples more efficiently, and\nwith the help tensor computation via torch these large\nposterior samples are computed quicker and more efficiently.\nFurthermore, the package provides model application and\nevaluation tools to guide the user in model selection, as well\nas making inferences from model output to generate robust\nestimations of intensity-duration-frequency curves.",
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      "arch": "x86_64",
      "commit": "e9c13a7f17e12b3fbc12a6aded54dbb4d2a90f48",
      "fileid": "770f8004e2debb0f71e58d7f68197180e7144b14352423bef4f22f261a2ff6b6",
      "status": "success",
      "check": "WARNING",
      "buildurl": "https://github.com/r-universe/alexleer/actions/runs/27054397619"
    }
  ]
}