{"title":"时变线性过程的自举泛函中心极限定理","authors":"Carina Beering, Anne Leucht","doi":"10.1080/10485252.2023.2284896","DOIUrl":null,"url":null,"abstract":"We provide a functional central limit theorem for a broad class of smooth functions for possibly non-causal multivariate linear processes with time-varying coefficients. Since the limiting processe...","PeriodicalId":50112,"journal":{"name":"Journal of Nonparametric Statistics","volume":"93 ","pages":""},"PeriodicalIF":0.8000,"publicationDate":"2023-11-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"A bootstrap functional central limit theorem for time-varying linear processes\",\"authors\":\"Carina Beering, Anne Leucht\",\"doi\":\"10.1080/10485252.2023.2284896\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"We provide a functional central limit theorem for a broad class of smooth functions for possibly non-causal multivariate linear processes with time-varying coefficients. Since the limiting processe...\",\"PeriodicalId\":50112,\"journal\":{\"name\":\"Journal of Nonparametric Statistics\",\"volume\":\"93 \",\"pages\":\"\"},\"PeriodicalIF\":0.8000,\"publicationDate\":\"2023-11-27\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Nonparametric Statistics\",\"FirstCategoryId\":\"100\",\"ListUrlMain\":\"https://doi.org/10.1080/10485252.2023.2284896\",\"RegionNum\":4,\"RegionCategory\":\"数学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"STATISTICS & PROBABILITY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Nonparametric Statistics","FirstCategoryId":"100","ListUrlMain":"https://doi.org/10.1080/10485252.2023.2284896","RegionNum":4,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"STATISTICS & PROBABILITY","Score":null,"Total":0}
A bootstrap functional central limit theorem for time-varying linear processes
We provide a functional central limit theorem for a broad class of smooth functions for possibly non-causal multivariate linear processes with time-varying coefficients. Since the limiting processe...
期刊介绍：
Journal of Nonparametric Statistics provides a medium for the publication of research and survey work in nonparametric statistics and related areas. The scope includes, but is not limited to the following topics:
Nonparametric modeling,
Nonparametric function estimation,
Rank and other robust and distribution-free procedures,
Resampling methods,
Lack-of-fit testing,
Multivariate analysis,
Inference with high-dimensional data,
Dimension reduction and variable selection,
Methods for errors in variables, missing, censored, and other incomplete data structures,
Inference of stochastic processes,
Sample surveys,
Time series analysis,
Longitudinal and functional data analysis,
Nonparametric Bayes methods and decision procedures,
Semiparametric models and procedures,
Statistical methods for imaging and tomography,
Statistical inverse problems,
Financial statistics and econometrics,
Bioinformatics and comparative genomics,
Statistical algorithms and machine learning.
Both the theory and applications of nonparametric statistics are covered in the journal. Research applying nonparametric methods to medicine, engineering, technology, science and humanities is welcomed, provided the novelty and quality level are of the highest order.
Authors are encouraged to submit supplementary technical arguments, computer code, data analysed in the paper or any additional information for online publication along with the published paper.
京公网安备 11010802042870号
京ICP备2023020795号-1
分享
求助内容：
应助结果提醒方式：
扫码关注我们
