On the Modelling and Prediction of High-Dimensional Functional Time Series

IF 3 1区数学 Q1 STATISTICS & PROBABILITY

Journal of the American Statistical Association Pub Date : 2024-10-15 DOI:10.1080/01621459.2024.2413201

Jinyuan Chang, Qin Fang, Xinghao Qiao, Qiwei Yao

引用次数: 0

Abstract

We propose a two-step procedure to model and predict high-dimensional functional time series, where the number of function-valued time series p is large in relation to the length of time series n. ...

查看原文本刊更多论文

论高维函数时间序列的建模与预测

我们提出了一个两步程序来模拟和预测高维函数时间序列，其中函数值时间序列的数量 p 相对于时间序列的长度 n 较大。

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

Journal of the American Statistical Association 数学-统计学与概率论

CiteScore

7.50

自引率

8.10%

发文量

168

审稿时长

12 months

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.