雜志介紹

Journal Of Nonparametric Statistics雜志介紹

《Journal Of Nonparametric Statistics》是一本以English為主的未開放獲取國際優秀期刊，中文名稱非參數統計雜志，本刊主要出版、報道數學-STATISTICS & PROBABILITY領域的研究動態以及在該領域取得的各方面的經驗和科研成果，介紹該領域有關本專業的最新進展，探討行業發展的思路和方法，以促進學術信息交流，提高行業發展。該刊已被國際權威數據庫SCIE收錄，為該領域相關學科的發展起到了良好的推動作用，也得到了本專業人員的廣泛認可。該刊最新影響因子為0.8，最新CiteScore 指數為1.5。

本刊近期中國學者發表的論文主要有：

• Inference on semi-parametric transformation model with a pairwise likelihood based on left-truncated and interval-censored data

  Author: Lou, Yichen; Wang, Peijie; Sun, Jianguo

• Regression analysis of mixed panel count data with dependent observation processes

  Author: Ge, Lei; Choi, Jaihee; Zhao, Hui; Li, Yang; Sun, Jianguo

• Choosing shape parameters for regression in reproducing kernel Hilbert space and variable selection

  Author: Tan, Xin; Xia, Yingcun; Kong, Efang

• Asymptotic behaviour of the portmanteau tests in an integer-valued AR model

  Author: Zhang, Jing; Li, Bo; Liu, Xiaohui; Wan, Xinyue

英文介紹

Journal Of Nonparametric Statistics雜志英文介紹

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.