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Model averaging for interval-valued data

文献类型：期刊论文

作者Sun, Yuying1,2,3; Zhang, Xinyu1,2,4; Wan, Alan T. K.5; Wang, Shouyang1,2,3
刊名EUROPEAN JOURNAL OF OPERATIONAL RESEARCH
出版日期2022-09-01
卷号301期号:2页码:772-784
关键词Forecasting Asymptotic optimality Interval-valued time series Model averaging Vector autoregression
ISSN号0377-2217
DOI10.1016/j.ejor.2021.11.015
英文摘要In recent years, model averaging, by which estimates are obtained based on not one single model but a weighted ensemble of models, has received growing attention as an alternative to model selection. To date, methods for model averaging have been developed almost exclusively for point-valued data, despite the fact that interval-valued data are commonplace in many applications and the substantial body of literature on estimation and inference methods for interval-valued data. This paper focuses on the special case of interval time series data, and assumes that the mid-point and log-range of the interval values are modelled by a two-equation vector autoregressive with exogenous covariates (VARX) model. We develop a methodology for combining models of varying lag orders based on a weight choice criterion that minimises an unbiased estimator of the squared error risk of the model average estimator. We prove that this method yields predictors of mid-points and ranges with an optimal asymptotic property. In addition, we develop a method for correcting the range forecasts, taking into account the forecast error variance. An extensive simulation experiment examines the performance of the proposed model averaging method in finite samples. We apply the method to an interval-valued data series on crude oil future prices.(c) 2021 Published by Elsevier B.V.
资助项目National Natural Science Foundation of China (NNSFC)[72073126] ; National Natural Science Foundation of China (NNSFC)[72091212] ; National Natural Science Foundation of China (NNSFC)[71925007] ; National Natural Science Foundation of China (NNSFC)[71631008] ; National Natural Science Foundation of China (NNSFC)[11688101] ; National Natural Science Foundation of China (NNSFC)[71973116] ; National Natural Science Foundation of China (NNSFC)[71988101] ; Fundamental Research Funds for the Central Universities in UIBE[19YB26] ; Hong Kong Research Grants Council[CityU 11500419] ; National Key R&D Program of China[2020AAA0105200] ; Academy for Multidisciplinary Studies, Capital Normal University
WOS研究方向Business & Economics ; Operations Research & Management Science
语种英语
WOS记录号WOS:000793723100026
出版者ELSEVIER
源URL[http://ir.amss.ac.cn/handle/2S8OKBNM/61321]  
专题中国科学院数学与系统科学研究院
通讯作者Zhang, Xinyu
作者单位1.Chinese Acad Sci, Acad Math & Syst Sci, Beijing, Peoples R China
2.Chinese Acad Sci, Ctr Forecasting Sci, Beijing, Peoples R China
3.Univ Chinese Acad Sci, Sch Econ & Management, Beijing, Peoples R China
4.Beijing Acad Artificial Intelligence, Beijing, Peoples R China
5.City Univ Hong Kong, Dept Management Sci, Hong Kong, Peoples R China
推荐引用方式
GB/T 7714		 Sun, Yuying,Zhang, Xinyu,Wan, Alan T. K.,et al. Model averaging for interval-valued data[J]. EUROPEAN JOURNAL OF OPERATIONAL RESEARCH,2022,301(2):772-784.
APA Sun, Yuying,Zhang, Xinyu,Wan, Alan T. K.,&Wang, Shouyang.(2022).Model averaging for interval-valued data.EUROPEAN JOURNAL OF OPERATIONAL RESEARCH,301(2),772-784.
MLA Sun, Yuying,et al."Model averaging for interval-valued data".EUROPEAN JOURNAL OF OPERATIONAL RESEARCH 301.2(2022):772-784.

入库方式： OAI收割

来源：数学与系统科学研究院

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