Statistics and its Interface

Top Research Topics at Statistics and Its Interface?

The scientific interests tackled in Statistics and Its Interface are Statistics, Econometrics, Artificial intelligence, Applied mathematics and Bayesian probability. The journal concentrates on Statistics topics that focus on Covariate, Multivariate statistics, Empirical likelihood, Nonparametric statistics and Missing data. The concepts on Econometrics presented in Statistics and Its Interface can also apply to other research fields, including Regression analysis and Estimator.

The journal explores issues in Artificial intelligence which can be linked to other research areas like Machine learning and Pattern recognition. Specifically, studies on Markov chain Monte Carlo are prevalent in the Bayesian probability works discussed.

• Statistics (39.64%)
• Econometrics (24.56%)
• Artificial intelligence (12.72%)

What are the most cited papers published in the journal?

• Multi-class AdaBoost ∗ (949 citations)
• Conceptual issues concerning mediation, interventions and composition (418 citations)
• Statistical Methods with Varying Coefficient Models. (290 citations)

Research areas of the most cited articles at Statistics and Its Interface:

The journal articles focus largely on the fields of Econometrics, Statistics, Algorithm, Singular spectrum analysis and Series (mathematics). The most cited publications investigate Econometrics research which frequently intersects with Inference. While work presented in the published papers provide substantial information on Algorithm, it also covers topics in Estimator and Lasso (statistics), Artificial intelligence.

What topics the last edition of the journal is best known for?

• Statistics
• Normal distribution
• Machine learning

The previous edition focused in particular on these issues:

The main points discussed in Statistics and Its Interface deals with Applied mathematics, Algorithm, Bayes estimator, Statistics and Gibbs sampling. Some problems in Applied mathematics that were presented in Statistics and Its Interface overlapped with concepts under Leverage effect, Diffusion process, Statistical inference and Leverage (statistics). The research on Algorithm featured in it combines topics in other fields like Semiparametric model, Markov chain Monte Carlo, Computerized testing, Accelerated failure time model and Survival data.

While Bayes estimator is the focus of the journal, it also provided insights into the studies of Mcmc algorithm, Double threshold, Moving average and Selection (genetic algorithm). Statistics and Its Interface explores research in Statistics and the adjacent study of Risk measure. While work presented in Statistics and Its Interface provided substantial information on Gibbs sampling, it also covered topics in Uniformization (probability theory), B-spline and Autoregressive model.

The most cited articles from the last journal are:

• Rate-efficient asymptotic normality for the Fourier estimator of the leverage process (1 citations)
• Sparsity-restricted estimation for the accelerated failure time model (0 citations)
• Pathway Lasso: pathway estimation and selection with high-dimensional mediators (0 citations)

Papers citation over time

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.

Top authors and change over time

The top authors publishing in Statistics and Its Interface (based on the number of publications) are:

• Yong Zhou (12 papers) absent at the last edition,
• Guo-Liang Tian (11 papers) absent at the last edition,
• Heping Zhang (11 papers) absent at the last edition,
• Hansheng Wang (11 papers) absent at the last edition,
• Ming-Hui Chen (9 papers) published 1 paper at the last edition.

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.

Top affiliations and change over time

Only papers with recognized affiliations are considered

The top affiliations publishing in Statistics and Its Interface (based on the number of publications) are:

• Yale University (26 papers) absent at the last edition,
• Peking University (25 papers) absent at the last edition,
• University of Connecticut (25 papers) published 2 papers at the last edition, 1 less than at the previous edition,
• University of Hong Kong (21 papers) published 1 paper at the last edition the same number as at the previous edition,
• University of North Carolina at Chapel Hill (21 papers) absent at the last edition.

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.

Publication chance based on affiliation

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 2022 edition, 10.00% of publications had an unrecognized affiliation. Out of the publications with recognized affiliations, 33.33% were posted by at least one author from the top 10 institutions publishing in the journal. Another 0.00% included authors affiliated with research institutions from the top 11-20 affiliations. Institutions from the 21-50 range included 22.22% of all publications and 44.44% were from other institutions.

Returning Authors Index

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.

Returning Institution Index

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.

The experience to innovation index

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:

• Novice - P < 5 or C < 25 (the number of publications less than 5 or the number of citations less than 25),
• Competent - P < 10 or C < 100 (the number of publications less than 10 or the number of citations less than 100),
• Experienced - P < 25 or C < 625 (the number of publications less than 25 or the number of citations less than 625),
• Master - P < 50 or C < 2500 (the number of publications less than 50 or the number of citations less than 2500),
• Star - P ≥ 50 and C ≥ 2500 (both the number of publications greater than 50 and the number of citations greater than 2500).

The chart below illustrates experience levels of first authors in cases of publications with multiple authors.