| Discipline name | Position | Best Scientists | Publications | D-Index |
|---|---|---|---|---|
| Mathematics | 669 | 9 | 11 | 3 |
The scientific interests tackled in Journal of The Korean Statistical Society are Bayesian inference, Statistics, Applied mathematics, Estimator and Econometrics. The journal addresses concerns in Bayesian inference which are intertwined with other disciplines, such as Nonparametric statistics, Covariate, Mathematical optimization, Autoregressive model and Algorithm. Topics like Asymptotic distribution, Quantile, Regression analysis, Empirical likelihood and Statistic are tackled as part of the discussions on Statistics.
Some problems in Applied mathematics that were presented in Journal of The Korean Statistical Society overlapped with concepts under Linear model and Linear regression. The research on Estimator featured in the journal combines topics in other fields like Mean squared error and Parametric statistics.
The most cited papers mainly deal with areas of study such as Bayesian inference, Statistics, Estimator, Mathematical optimization and Mathematical analysis. The journal papers facilitate discussions on Bayesian inference that incorporate concepts from other fields like Statistical hypothesis testing, Econometrics, Cluster analysis, Distribution (number theory) and Algorithm. Most of the works presented in the journal papers deal with Statistics but they intersect with the subject of Combinatorics.
The journal focuses largely on the fields of Bayesian inference, Statistics, Applied mathematics, Estimator and Econometrics. Research in Covariate and the interrelating topic of Missing data were among the subjects of interest in the Bayesian inference studies discussed in the journal. Confidence interval, Quantile, Empirical likelihood, Sample size determination and Multivariate statistics are all aspects of Statistics research featured in the journal.
While Applied mathematics is the focus of the journal, it also provided insights into the studies of Nonparametric statistics, Linear model, Linear regression and Consistency (statistics). The work on Nonparametric statistics tackled in it brings together disciplines like Smoothing, Statistical hypothesis testing and Parametric statistics. In addition to Estimator research, it aims to explore topics under Positive-definite matrix, Outlier, Maximum likelihood, Covariance matrix and Range (statistics).
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 The Korean Statistical Society (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 The Korean Statistical Society (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, 4.76% of publications had an unrecognized affiliation. Out of the publications with recognized affiliations, 43.75% were posted by at least one author from the top 10 institutions publishing in the journal. Another 7.50% included authors affiliated with research institutions from the top 11-20 affiliations. Institutions from the 21-50 range included 8.75% of all publications and 40.00% 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.
Wilson Y. Chen;Matt P. Wand
(2020)Hohsuk Noh;Ingrid Van Keilegom
(2020)Solt Kovács;Housen Li;Peter Bühlmann
(2020)Peijie Wang;Peijie Wang;Yong Zhou;Jianguo Sun
(2020)Tianqing Liu;Xiaohui Yuan;Jianguo Sun
(2021)Mahsa Sasaei;Reza Pourmousa;Narayanaswamy Balakrishnan;Ahad Jamalizadeh
(2021)Y. K. Lee;H. Hong;D. Kim;B. U. Park
(2021)Pursuing a degree in Mathematics opens diverse career opportunities, from data analysis to finance and technology. For those interested in a more specialized field, an online sports management degree offers a unique blend of business and athletics, ideal for combining passion with professionalism.
If flexibility and speed are priorities, exploring the online math degree programs can be a great choice, providing quality education with the convenience to study from anywhere. Many students also consider advancing to business leadership roles by pursuing an MBA.
For those aiming to balance rigorous academics with manageable admissions, the easiest MBA programs provide accessible pathways to graduate business education. Alternatively, if speed is crucial, the fastest online MBA degree programs allow students to complete their studies quickly without compromising on content quality.
Choosing the right program depends on individual goals, career aspirations, and learning preferences. Exploring these related fields can help broaden career options and enhance professional growth.
