Journal Of Nonparametric Statistics

杂志介绍

Journal Of Nonparametric Statistics杂志介绍

《Journal Of Nonparametric Statistics》是一本以English为主的未开放获取国际优秀期刊，中文名称非参数统计杂志，本刊主要出版、报道数学-STATISTICS & PROBABILITY领域的研究动态以及在该领域取得的各方面的经验和科研成果，介绍该领域有关本专业的最新进展，探讨行业发展的思路和方法，以促进学术信息交流，提高行业发展。该刊已被国际权威数据库SCIE收录，为该领域相关学科的发展起到了良好的推动作用，也得到了本专业人员的广泛认可。该刊最新影响因子为0.8，最新CiteScore 指数为1.5。

本刊近期中国学者发表的论文主要有：

• 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

英文介绍

Journal Of Nonparametric Statistics杂志英文介绍

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.