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  "Title": "Generalized L-Moments Estimation for Extreme Value Distributions",
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  "Description": "Provides generalized L-moments estimation methods for the\ngeneralized extreme value ('GEV') distribution. Implements both\nstationary 'GEV' and non-stationary 'GEV11' models where\nlocation and scale parameters vary with time. Includes various\npenalty functions (Martins-Stedinger, Park, Cannon,\nColes-Dixon) for shape parameter regularization. Also provides\nmodel averaging estimation ('ma.gev') that combines MLE and\nL-moment methods with multiple weighting schemes for robust\nhigh quantile estimation. The 'GLME' methodology is described\nin Shin et al. (2025a) <doi:10.48550/arXiv.2512.20385>. The\nnon-stationary L-moment method is based on Shin et al. (2025b)\n<doi:10.1007/s42952-025-00325-3>. The model averaging method is\ndescribed in Shin et al. (2026)\n<doi:10.1007/s00477-025-03167-x>. See also Hosking (1990)\n<doi:10.1111/j.2517-6161.1990.tb01775.x> for L-moments theory\nand Martins and Stedinger (2000) <doi:10.1029/1999WR900330> for\npenalized likelihood methods.",
  "License": "GPL (>= 3)",
  "URL": "https://github.com/sygstat/GLmom",
  "BugReports": "https://github.com/sygstat/GLmom/issues",
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  "Date/Publication": "2026-07-28 01:21:47 UTC",
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      "title": "Generalized L-moments estimation for generalized extreme value distribution",
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