更正“用统计和机器学习模型评估环境时间序列的可预测性”

IF 1.5 3区环境科学与生态学 Q4 ENVIRONMENTAL SCIENCES

Environmetrics Pub Date : 2025-02-27 DOI:10.1002/env.70008

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引用次数: 0

摘要

纽兰兹，N.K.和吕布奇，V. 2025。“用统计和机器学习模型评估环境时间序列的可预测性。”环境科学学报，36(2),393 - 393。https://doi.org/10.1002/env.70000.In这篇文章最初发布的版本，标题是错误的。下面是更正后的文章标题：关于“用统计和机器学习模型评估环境时间序列的可预测性”的讨论，我们为这个错误道歉。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

查看原文本刊更多论文

Correction to “Assessing Predictability of Environmental Time Series With Statistical and Machine Learning Models”

Newlands, N.K. and Lyubchich, V. 2025. “ Assessing Predictability of Environmental Time Series With Statistical and Machine Learning Models.” Environmetrics 36(2), e70000. https://doi.org/10.1002/env.70000.

In the initial published version of this article, the title was incorrect. Below is the corrected article title:

Discussion on “Assessing Predictability of Environmental Time Series With Statistical and Machine Learning Models”

We apologize for this error.

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来源期刊

Environmetrics 环境科学-环境科学

CiteScore

2.90

自引率

17.60%

发文量

审稿时长

18-36 weeks

期刊介绍： Environmetrics, the official journal of The International Environmetrics Society (TIES), an Association of the International Statistical Institute, is devoted to the dissemination of high-quality quantitative research in the environmental sciences. The journal welcomes pertinent and innovative submissions from quantitative disciplines developing new statistical and mathematical techniques, methods, and theories that solve modern environmental problems. Articles must proffer substantive, new statistical or mathematical advances to answer important scientific questions in the environmental sciences, or must develop novel or enhanced statistical methodology with clear applications to environmental science. New methods should be illustrated with recent environmental data.