Efficient estimation of return value distributions from non-stationary marginal extreme value models using Bayesian inference

Ross Emma; Randell David; Ewans Kevin; Feld Graham; Jonathan Philip

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Efficient estimation of return value distributions from non-stationary marginal extreme value models using Bayesian inference

机译：使用贝叶斯推断从非平稳边际极值模型中有效估算收益值分布

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Extreme values of an environmental response can be estimated by fitting the generalised Pareto distribution to a sample of exceedances of a high threshold. In oceanographic applications to responses such as ocean storm severity, threshold and model parameters are typically functions of physical covariates. A fundamental difficulty is selection or estimation of an appropriate threshold or interval of thresholds, of particular concern since inferences for return values vary with threshold choice. Historical studies suggest that evidence for threshold selection is weak in typical samples.

机译：可以通过将广义帕累托分布拟合到高阈值超出的样本来估计环境响应的极值。在海洋应用中，如对海洋风暴严重性的响应，阈值和模型参数通常是物理协变量的函数。一个基本的困难是选择或估计适当的阈值或阈值间隔，这特别值得关注，因为返回值的推论随阈值选择而变化。历史研究表明，在典型样本中，阈值选择的证据很少。

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来源
《Ocean Engineering》 |2017年第15期|315-328|共14页
作者
Ross Emma; Randell David; Ewans Kevin; Feld Graham; Jonathan Philip;
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作者单位

Shell Projects & Technol, London SE1 7NA, England;

Shell Projects & Technol, NL-1031 HW Amsterdam, Netherlands;

Metocean Res Ltd, New Plymouth 4310, New Zealand;

Shell Projects & Technol, Aberdeen AB12 3FY, Scotland;

Shell Projects & Technol, London SE1 7NA, England;

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原文格式 PDF
正文语种 eng
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关键词
Extreme; Significant wave height; Non-stationary; Splines; Bayesian inference; Return value; Numerical integration;

机译：极高;显着波高;非平稳;样条曲线;贝叶斯推断;返回值;数值积分;

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机译：贝叶斯推断非平稳边际极值

Efficient estimation of return value distributions from non-stationary marginal extreme value models using Bayesian inference

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