雜志介紹

Journal Of Time Series Analysis雜志介紹

《Journal Of Time Series Analysis》是(shi)一本(ben)以English為主的(de)(de)(de)(de)未開放獲取(qu)國(guo)際優秀期刊，中(zhong)文名稱時間序列分析雜志(zhi)，本(ben)刊主要出版、報道數學-MATHEMATICS, INTERDISCIPLINARY APPLICATIONS領域的(de)(de)(de)(de)研究動(dong)態以及在該(gai)領域取(qu)得(de)的(de)(de)(de)(de)各方(fang)面的(de)(de)(de)(de)經驗(yan)和科研成果(guo)，介(jie)紹(shao)該(gai)領域有關(guan)本(ben)專(zhuan)業的(de)(de)(de)(de)最(zui)新(xin)進展，探討行(xing)業發展的(de)(de)(de)(de)思路和方(fang)法，以促進學術信息交(jiao)流，提(ti)高行(xing)業發展。該(gai)刊已被國(guo)際權威數據庫SCIE收錄，為該(gai)領域相關(guan)學科的(de)(de)(de)(de)發展起(qi)到(dao)了良好的(de)(de)(de)(de)推(tui)動(dong)作用(yong)，也(ye)得(de)到(dao)了本(ben)專(zhuan)業人(ren)員的(de)(de)(de)(de)廣泛(fan)認可(ke)。該(gai)刊最(zui)新(xin)影(ying)響(xiang)因子(zi)為1.2，最(zui)新(xin)CiteScore 指(zhi)數為2。

本刊近期(qi)中國學(xue)者發表的論文主(zhu)要有(you)：

• Higher-order asymptotics of minimax estimators for time series

  Author: Xu, Xiaofei; Liu, Yan; Taniguche, Masanobu

• Geometric ergodicity and conditional self-weighted M-estimator of a GRCAR(p) model with heavy-tailed errors

  Author: Li, Xiaoyan; Pan, Jiazhu; Song, Anchao

• Inference for high-dimensional linear models with locally stationary error processes

  Author: Xia, Jiaqi; Chen, Yu; Guo, Xiao

• Inference on a Structural Break in Trend with Fractionally Integrated Errors

  Author: sychang

英文介紹

Journal Of Time Series Analysis雜志英文介紹

During the last 30 years Time Series Analysis has become one of the most important and widely used branches of Mathematical Statistics. Its fields of application range from neurophysiology to astrophysics and it covers such well-known areas as economic forecasting, study of biological data, control systems, signal processing and communications and vibrations engineering.

The Journal of Time Series Analysis started in 1980, has since become the leading journal in its field, publishing papers on both fundamental theory and applications, as well as review papers dealing with recent advances in major areas of the subject and short communications on theoretical developments. The editorial board consists of many of the world's leading experts in Time Series Analysis.