{"title":"Utilizarea teoriei valorilor extreme în climatologie","authors":"Valentina Raileanu","doi":"10.53380/9789975315593.17","DOIUrl":null,"url":null,"abstract":"The article briefly describes the history and fields of application of the theory of extreme values, including climatology. The data format, the Generalized Extreme Value (GEV) probability distributions with Bock Maxima, the Generalized Pareto (GP) distributions with Point of Threshold (POT) and the analysis methods are presented. Estimating the distribution parameters is done using the Maximum Likelihood Estimation (MLE) method. Free R software installation, the minimum set of required commands and the GUI in2extRemes graphical package are described. As an example, the results of the GEV analysis of a simulated data set in in2extRemes are presented.","PeriodicalId":402313,"journal":{"name":"Starea actuală a componentelor de mediu","volume":"5 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Starea actuală a componentelor de mediu","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.53380/9789975315593.17","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

摘要

本文简要介绍了极值理论的历史和应用领域,包括气候学。给出了数据格式、具有Bock极大值的广义极值(GEV)概率分布、具有阈值点(POT)的广义Pareto (GP)分布及其分析方法。分布参数的估计采用最大似然估计(MLE)方法。介绍了免费的R软件安装、所需的最小命令集和GUI in2extRemes图形包。作为实例,给出了in2extRemes模拟数据集的GEV分析结果。
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Utilizarea teoriei valorilor extreme în climatologie
The article briefly describes the history and fields of application of the theory of extreme values, including climatology. The data format, the Generalized Extreme Value (GEV) probability distributions with Bock Maxima, the Generalized Pareto (GP) distributions with Point of Threshold (POT) and the analysis methods are presented. Estimating the distribution parameters is done using the Maximum Likelihood Estimation (MLE) method. Free R software installation, the minimum set of required commands and the GUI in2extRemes graphical package are described. As an example, the results of the GEV analysis of a simulated data set in in2extRemes are presented.
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