The generalized extreme value (GEV) distribution is commonly employed to help estimate the likelihood of extreme events in many geophysical and other application areas. The recently proposed blended generalized extreme value (bGEV) distribution modifies the GEV with positive shape parameter to avoid a hard lower bound that complicates fitting and inference. Here, the bGEV is extended to the GEV with negative shape parameter, avoiding a hard upper bound that is unrealistic in many applications. This extended bGEV is shown to improve on the GEV for forecasting future heat extremes based on past data. Software implementing this bGEV and applying it to the example temperature data is provided.

翻译：广义极值（GEV）分布常用于估计地球物理学及其他应用领域中极端事件的发生概率。最近提出的混合广义极值（bGEV）分布对具有正形状参数的GEV分布进行了修正，以避免因存在硬性下界而导致的拟合与推断困难。本文进一步将bGEV扩展至具有负形状参数的GEV分布，从而规避了在许多实际应用中不符合现实的硬性上界。研究表明，基于历史数据预测未来极端高温事件时，这种扩展的bGEV分布相较于传统GEV分布具有更优性能。文中同时提供了实现该bGEV分布并将其应用于示例温度数据的相关软件。