极端随机森林

IF 3 1区数学 Q1 STATISTICS & PROBABILITY

Journal of the American Statistical Association Pub Date : 2024-01-08 DOI:10.1080/01621459.2023.2300522

Nicola Gnecco, Edossa Merga Terefe, Sebastian Engelke

引用次数: 0

摘要

当所关注的量值是极值，只有少数或没有训练数据点超过该量值时，量值回归的经典方法就会失效。极值理论的渐近结果可以...

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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Extremal Random Forests

Classical methods for quantile regression fail in cases where the quantile of interest is extreme and only few or no training data points exceed it. Asymptotic results from extreme value theory can...

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来源期刊

Journal of the American Statistical Association 数学-统计学与概率论

CiteScore

7.50

自引率

8.10%

发文量

168

审稿时长

12 months

期刊介绍： Established in 1888 and published quarterly in March, June, September, and December, the Journal of the American Statistical Association ( JASA ) has long been considered the premier journal of statistical science. Articles focus on statistical applications, theory, and methods in economic, social, physical, engineering, and health sciences. Important books contributing to statistical advancement are reviewed in JASA . JASA is indexed in Current Index to Statistics and MathSci Online and reviewed in Mathematical Reviews. JASA is abstracted by Access Company and is indexed and abstracted in the SRM Database of Social Research Methodology.