Estimating GEV Parameters

This lecture covers the estimation of Generalized Extreme Value (GEV) parameters using various techniques such as graphical methods, moment-based estimators, L-moments, and likelihood-based approaches. It explores the use of quantile-quantile plots, Gumbel plotting positions, and Hill estimators for inference on extreme values. The lecture also discusses the application of these methods to real-world data, illustrated with examples like Venezuela rainfall. Additionally, it delves into the challenges of fitting extreme value models and interpreting results, emphasizing the importance of confidence intervals and model stability.