A review of flow field forecasting: A high‐dimensional forecasting procedure

IF 4.4 2区 数学 Q1 STATISTICS & PROBABILITY
Kyle A. Caudle, Patrick S. Fleming, R. Hoover
{"title":"A review of flow field forecasting: A high‐dimensional forecasting procedure","authors":"Kyle A. Caudle, Patrick S. Fleming, R. Hoover","doi":"10.1002/wics.1505","DOIUrl":null,"url":null,"abstract":"Forecasting, especially high‐dimensional forecasting, is becoming more and more sought after, particularly as computing resources increase in both size and speed. Flow field forecasting is a general purpose regression‐based forecasting method that has recently been expanded to high‐dimensional settings. In this article, we provide an overview of the flow field forecasting methodology, with a particular emphasis on environments where the number of candidate predictor variables is large, potentially larger than the number of observations.","PeriodicalId":47779,"journal":{"name":"Wiley Interdisciplinary Reviews-Computational Statistics","volume":null,"pages":null},"PeriodicalIF":4.4000,"publicationDate":"2020-02-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1002/wics.1505","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Wiley Interdisciplinary Reviews-Computational Statistics","FirstCategoryId":"100","ListUrlMain":"https://doi.org/10.1002/wics.1505","RegionNum":2,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"STATISTICS & PROBABILITY","Score":null,"Total":0}
引用次数: 1

Abstract

Forecasting, especially high‐dimensional forecasting, is becoming more and more sought after, particularly as computing resources increase in both size and speed. Flow field forecasting is a general purpose regression‐based forecasting method that has recently been expanded to high‐dimensional settings. In this article, we provide an overview of the flow field forecasting methodology, with a particular emphasis on environments where the number of candidate predictor variables is large, potentially larger than the number of observations.
流场预测综述:一种高维预测方法
预测,尤其是高维预测,正变得越来越受追捧,特别是随着计算资源在规模和速度上的增加。流场预测是一种基于回归的通用预测方法,最近已扩展到高维设置。在本文中,我们概述了流场预测方法,特别强调了候选预测变量数量很大的环境,可能大于观测值的数量。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
CiteScore
6.20
自引率
0.00%
发文量
31
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信