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This lecture introduces L-moment estimation, defining probability-weighted moments and their application in fitting GEV and GPD distributions. It covers the linear L-moment estimators' robustness and small-sample properties, contrasting them with ordinary moment estimators. Likelihood inference basics, maximum likelihood estimation, and model diagnostics are also discussed.
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