| Discipline name | Position | Best Scientists | Publications | D-Index |
|---|---|---|---|---|
| Mathematics | 445 | 22 | 32 | 6 |
Statistical Modelling covers a variety of subjects, including Statistics, Econometrics, Bayesian probability, Applied mathematics and Artificial intelligence. Statistical Modelling facilitated discussions that integrated Statistics and Random effects model. While it primarily focused on Random effects model, it also opened dialogues on the discipline of Generalized linear mixed model.
Statistical Modelling addresses concerns in Econometrics which are intertwined with other disciplines, such as Categorical variable, Mixed model and Missing data. Markov chain Monte Carlo and Bayesian inference studies are all carried out as a component of the study in Bayesian probability presented. It focused on Markov chain Monte Carlo research but expanded to cover Algorithm.
The study on Applied mathematics presented in it intersects with subjects under the field of Mathematical optimization. Artificial intelligence research presented in Statistical Modelling encompasses a variety of subjects, including Machine learning and Pattern recognition.
The most cited papers are organized to reinforce research efforts on Statistics, Econometrics, Poisson distribution, Mathematical optimization and Random effects model. Logistic regression, Series (mathematics) and Bayesian probability, Markov chain Monte Carlo are some topics wherein Econometrics research discussed in the journal articles has an impact. In addition to Poisson distribution research, the journal publications aim to explore topics under Smoothing and Poisson regression.
The main points discussed in Statistical Modelling deals with Econometrics, Statistics, Bayesian probability, Multivariate statistics and Mixture model. Some problems in Econometrics that were presented in it overlapped with concepts under Basis (linear algebra), Regression analysis, Parametric statistics and Bayesian inference. The studies tackled, which mainly focus on Statistics, apply to Poisson regression as well.
While it focused on Bayesian probability, it was also able to explore topics like Data mining, Cause of death, Latent variable and Joint (audio engineering). The journal deals with Multivariate statistics in conjunction with Pattern recognition and similar fields in Object (computer science). The overlapping concepts between Expectation–maximization algorithm and Artificial intelligence, Estimating equations and Categorical variable are the key highlights of Mixture model study.
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 Statistical Modelling (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 Statistical Modelling (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, 2.63% of publications had an unrecognized affiliation. Out of the publications with recognized affiliations, 35.14% were posted by at least one author from the top 10 institutions publishing in the journal. Another 18.92% included authors affiliated with research institutions from the top 11-20 affiliations. Institutions from the 21-50 range included 13.51% of all publications and 32.43% 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.
Alexander Razen;Stefan Lang
(2020)Cathy Ws Chen;K Khamthong;K Khamthong
(2020)Tuhin Sheikh;Joseph G. Ibrahim;Jonathan A. Gelfond;Wei Sun
(2021)Elena Tuzhilina;Leonardo Tozzi;Trevor Hastie
(2021)Stanislaus Stadlmann;Thomas Kneib
(2021)Elmar Spiegel;Thomas Kneib;Fabian Otto-Sobotka
(2020)Mohsen Maleki;Geoffrey J. McLachlan;Sharon X. Lee
(2021)M. Menictas;T. H. Nolan;T. H. Nolan;D. G. Simpson;M. P. Wand;M. P. Wand
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