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  "Title": "Likelihood-Based Inference for Time Series Extremes",
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  "Date": "2026-01-24",
  "Authors@R": "person(c(\"Paul\", \"J.\"), \"Northrop\", email = \"p.northrop@ucl.ac.uk\",\nrole = c(\"aut\", \"cre\", \"cph\"))",
  "Description": "Performs likelihood-based inference for stationary time\nseries extremes.  The general approach follows Fawcett and\nWalshaw (2012) <doi:10.1002/env.2133>.  Marginal extreme value\ninferences are adjusted for cluster dependence in the data\nusing the methodology in Chandler and Bate (2007)\n<doi:10.1093/biomet/asm015>, producing an adjusted\nlog-likelihood for the model parameters.  A log-likelihood for\nthe extremal index is produced using the K-gaps model of\nSuveges and Davison (2010) <doi:10.1214/09-AOAS292>. These\nlog-likelihoods are combined to make inferences about extreme\nvalues. Both maximum likelihood and Bayesian approaches are\navailable.",
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