{"title":"有监督的动态 PCA：多预测因子线性动态预测","authors":"Zhaoxing Gao, Ruey S. Tsay","doi":"10.1080/01621459.2024.2370592","DOIUrl":null,"url":null,"abstract":"This paper proposes a novel dynamic forecasting method using a new supervised Principal Component Analysis (PCA) when a large number of predictors are available. The new supervised PCA provides an ...","PeriodicalId":17227,"journal":{"name":"Journal of the American Statistical Association","volume":"33 1","pages":""},"PeriodicalIF":3.0000,"publicationDate":"2024-06-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Supervised Dynamic PCA: Linear Dynamic Forecasting with Many Predictors\",\"authors\":\"Zhaoxing Gao, Ruey S. Tsay\",\"doi\":\"10.1080/01621459.2024.2370592\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper proposes a novel dynamic forecasting method using a new supervised Principal Component Analysis (PCA) when a large number of predictors are available. The new supervised PCA provides an ...\",\"PeriodicalId\":17227,\"journal\":{\"name\":\"Journal of the American Statistical Association\",\"volume\":\"33 1\",\"pages\":\"\"},\"PeriodicalIF\":3.0000,\"publicationDate\":\"2024-06-24\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of the American Statistical Association\",\"FirstCategoryId\":\"100\",\"ListUrlMain\":\"https://doi.org/10.1080/01621459.2024.2370592\",\"RegionNum\":1,\"RegionCategory\":\"数学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"STATISTICS & PROBABILITY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of the American Statistical Association","FirstCategoryId":"100","ListUrlMain":"https://doi.org/10.1080/01621459.2024.2370592","RegionNum":1,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"STATISTICS & PROBABILITY","Score":null,"Total":0}
Supervised Dynamic PCA: Linear Dynamic Forecasting with Many Predictors
This paper proposes a novel dynamic forecasting method using a new supervised Principal Component Analysis (PCA) when a large number of predictors are available. The new supervised PCA provides an ...
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.
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