| Discipline name | Position | Best Scientists | Publications | D-Index |
|---|---|---|---|---|
| Mathematics | 494 | 18 | 24 | 5 |
Journal of Nonparametric Statistics is mainly concerned with subjects like Statistics, Estimator, Applied mathematics, Nonparametric statistics and Econometrics. The presentations discussing Statistics offer insights in topics such as Nonparametric regression, Asymptotic distribution, Kernel (statistics), Quantile and Kernel regression. In addition to Nonparametric regression research, the journal aims to explore topics under Semiparametric regression, Principal component regression and Polynomial regression.
Variable kernel density estimation is a major topic of Kernel (statistics) research presented in Journal of Nonparametric Statistics. It explores issues in Variable kernel density estimation which can be linked to other research areas like Kernel embedding of distributions and Kernel smoother. Estimator research featured in the journal incorporates concerns from various other topics such as Mean squared error, Rate of convergence and Smoothing.
The subject of Mathematical optimization, which is connected to the field of Algorithm, serves as the foundation of the Applied mathematics research featured in Journal of Nonparametric Statistics. In it, Multivariate statistics, Parametric statistics and Statistical hypothesis testing are investigated in conjunction with one another to address concerns in Nonparametric statistics research. Econometrics research is the primary subject tackled in it with a focus on Covariate.
The most cited publications mainly tackle studies in Statistics, Estimator, Applied mathematics, Nonparametric statistics and Mathematical optimization. The journal publications tackle studies in Econometrics and the interrelated subject of Linear regression to gain insights into Statistics. The most cited articles explore issues in Estimator which can be linked to other research areas like Kernel smoother, Outlier and Rate of convergence.
The aim of the journal is to expand the discussion of research in Statistics, Applied mathematics, Estimator, Empirical likelihood and Nonparametric statistics. Journal of Nonparametric Statistics facilitates discussions on Statistics that incorporate concepts from other fields like Series (mathematics) and Inequality. While work presented in it provided substantial information on Applied mathematics, it also covered topics in Additive model, Law of the iterated logarithm, Two sample and Kernel (statistics).
Topics in Kernel (statistics) explored in the journal were investigated in conjunction with research in Nonparametric density estimation and Kernel density estimation. The close relationship between Multivariate statistics and Density estimation, Regression function, Partial derivative, Wavelet and Asymptotic distribution is one of the points of interest dissected in Estimator research. Some problems in Nonparametric statistics that were presented in Journal of Nonparametric Statistics overlapped with concepts under Point (geometry), Interval (mathematics) and Data set.
A key indicator for each journal is its effectiveness in reaching other researchers with the papers published at that venue.
The chart below presents the interquartile range (first quartile 25%, median 50% and third quartile 75%) of the number of citations of articles over time.
The top authors publishing in Journal of Nonparametric Statistics (based on the number of publications) are:
The overall trend for top authors publishing in this journal is outlined below. The chart shows the number of publications at each edition of the journal for top authors.
Only papers with recognized affiliations are considered
The top affiliations publishing in Journal of Nonparametric Statistics (based on the number of publications) are:
The overall trend for top affiliations publishing in this journal is outlined below. The chart shows the number of publications at each edition of the journal for top affiliations.
The publication chance index shows the ratio of articles published by the best research institutions in the journal edition to all articles published within that journal. The best research institutions were selected based on the largest number of articles published during all editions of the journal.
The chart below presents the percentage ratio of articles from top institutions (based on their ranking of total papers).Top affiliations were grouped by their rank into the following tiers: top 1-10, top 11-20, top 21-50, and top 51+. Only articles with a recognized affiliation are considered.
During the most recent 2021 edition, 0.00% of publications had an unrecognized affiliation. Out of the publications with recognized affiliations, 16.00% were posted by at least one author from the top 10 institutions publishing in the journal. Another 8.00% included authors affiliated with research institutions from the top 11-20 affiliations. Institutions from the 21-50 range included 12.00% of all publications and 64.00% were from other institutions.
A very common phenomenon observed among researchers publishing scientific articles is the intentional selection of journals they have already attended in the past. In particular, it is worth analyzing the case when the authors participate in the same journal from year to year.
The Returning Authors Index presented below illustrates the ratio of authors who participated in both a given as well as the previous edition of the journal in relation to all participants in a given year.
The graph below shows the Returning Institution Index, illustrating the ratio of institutions that participated in both a given and the previous edition of the conference in relation to all affiliations present in a given year.
Our experience to innovation index was created to show a cross-section of the experience level of authors publishing in a journal. The index includes the authors publishing at the last edition of a journal, grouped by total number of publications throughout their academic career (P) and the total number of citations of these publications ever received (C).
The group intervals were selected empirically to best show the diversity of the authors' experiences, their labels were selected as a convenience, not as judgment. The authors were divided into the following groups:
The chart below illustrates experience levels of first authors in cases of publications with multiple authors.
Jeffrey S. Racine;Qi Li;Karen X. Yan
(2020)Shuwei Li;Tao Hu;Jianguo Sun
(2020)Jiahua Chen;Pengfei Li;Yukun Liu;James V. Zidek
(2021)Mohamed Fihri;Abdelhadi Akharif;Amal Mellouk;Marc Hallin
(2020)Yuan Sun;Xuming He
(2021)Jingke Zhou;Lixing Zhu;Lixing Zhu
(2021)Ana M. Bianco;Graciela Boente;Wenceslao González-Manteiga;Ana Pérez-González
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