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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,\n'Coles'-Dixon) for shape parameter regularization. Also\nprovides model averaging estimation ('ma.gev') that combines\nMLE and L-moment methods with multiple weighting schemes for\nrobust high quantile estimation. The 'GLME' methodology is\ndescribed in Shin et al. (2025a)\n<doi:10.48550/arXiv.2512.20385>. The non-stationary L-moment\nmethod 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>\nfor penalized likelihood methods.",
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