Extending the blended generalized extreme value distribution

被引:0
|
作者
Nir Y. Krakauer [1 ]
机构
[1] The City College of New York,Department of Civil Engineering
来源
关键词
D O I
10.1007/s44290-024-00102-x
中图分类号
学科分类号
摘要
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 heat and sea level extremes based on past data. Software implementing this bGEV and applying it to the example temperature and sea level data is provided.
引用
收藏
相关论文
共 50 条
  • [41] Comparison of parameters of the generalized extreme value distribution associated with extreme rainfall events in Central America
    Guillen-Oviedo, Helen S.
    Cid-Serrano, Luis R.
    Alfaro-Martinez, Eric J.
    UNICIENCIA, 2020, 34 (01) : 111 - 128
  • [42] The effect of the generalized extreme value distribution parameter estimation methods in extreme wind speed prediction
    Soukissian, Takvor H.
    Tsalis, Christos
    NATURAL HAZARDS, 2015, 78 (03) : 1777 - 1809
  • [43] Modeling Extreme PM10 Concentration in Malaysia Using Generalized Extreme Value Distribution
    Hasan, Husna
    Mansor, Nadiah
    Salleh, Nur Hanim Mohd
    INTERNATIONAL CONFERENCE ON MATHEMATICS, ENGINEERING AND INDUSTRIAL APPLICATIONS 2014 (ICOMEIA 2014), 2015, 1660
  • [44] Numerical Convergence of the Block-Maxima Approach to the Generalized Extreme Value Distribution
    Faranda, Davide
    Lucarini, Valerio
    Turchetti, Giorgio
    Vaienti, Sandro
    JOURNAL OF STATISTICAL PHYSICS, 2011, 145 (05) : 1156 - 1180
  • [45] Modeling High-resolution SAR Images with Generalized Extreme Value Distribution
    Bai, Junwu
    Li, Yiqiong
    PROCEEDINGS OF 2016 IEEE ADVANCED INFORMATION MANAGEMENT, COMMUNICATES, ELECTRONIC AND AUTOMATION CONTROL CONFERENCE (IMCEC 2016), 2016, : 945 - 949
  • [46] A bayesian analysis of the annual maximum temperature using generalized extreme value distribution
    Hassen, Cheraitia
    MAUSAM, 2021, 72 (03): : 607 - 618
  • [47] Feeder Burden Rate and Calculation Method Based on Generalized Extreme Value Distribution
    Wu H.
    Wang J.
    Miao A.
    Yuan Y.
    Dianwang Jishu/Power System Technology, 2023, 47 (02): : 773 - 783
  • [48] An experiment in subjective graphical quantile estimation applied to the generalized extreme value distribution
    Bardsley, W.E.
    Pearson, C.P.
    Hydrological Sciences Journal, 1999, 44 (03): : 399 - 405
  • [49] AVO inversion based on generalized extreme value distribution with adaptive parameter estimation
    Zhang, Jiashu
    Lv, Songfeng
    Liu, Yang
    Hu, Guangmin
    JOURNAL OF APPLIED GEOPHYSICS, 2013, 98 : 11 - 20
  • [50] Tolerance Interval for the Mixture Normal Distribution Based on Generalized Extreme Value Theory
    Jiao, Junjun
    Guan, Ruijie
    MATHEMATICS, 2024, 12 (07)