| Discipline name | Position | Best Scientists | Publications | D-Index |
|---|---|---|---|---|
| Mathematics | 75 | 70 | 118 | 20 |
| Computer Science | 429 | 35 | 57 | 14 |
The main research concerns discussed in the journal are Algorithm, Mathematical optimization, Applied mathematics, Artificial intelligence and Statistics. While Algorithm is the focus of Statistics and Computing, it also provided insights into the studies of Markov chain Monte Carlo, Inference, Expectation–maximization algorithm, Bayesian inference and Particle filter. The journal explores issues in Markov chain Monte Carlo which can be linked to other research areas like Markov chain and Gibbs sampling.
Statistics and Computing emphasizes research on Markov chain, which includes concerns such as Markov model. Topics in Mathematical optimization explored in it were investigated in conjunction with research in Smoothing, Monte Carlo method, Importance sampling, Convergence (routing) and Function (mathematics). Monte Carlo integration is a focus of the Monte Carlo method works in Statistics and Computing.
The study on Applied mathematics presented is investigated in conjunction with research in Posterior probability. The research on Artificial intelligence featured in it combines topics in other fields like Machine learning and Pattern recognition. The journal dives deep in exploring the relationship between the study of Statistics and Econometrics.
The journal articles focus on Artificial intelligence, Mathematical optimization, Algorithm, Markov chain Monte Carlo and Applied mathematics. While the journal papers focused on Artificial intelligence, they were also able to explore topics like Machine learning and Pattern recognition. The journal articles explore research in Algorithm alongside concepts in Bayesian inference and other areas of study in Inference.
The journal is mainly concerned with subjects like Algorithm, Applied mathematics, Monte Carlo method, Estimator and Bayesian probability. The tackled Algorithm research is interrelated with Function (mathematics) which concerns subjects like Random variable and Discrete mathematics. The close relationship between Posterior probability and Distribution (mathematics) is one of the points of interest dissected in Applied mathematics research.
Monte Carlo method research is the primary subject tackled in Statistics and Computing with a focus on Markov chain Monte Carlo. Statistics and Computing focuses on Markov chain Monte Carlo but the discussions also offer insight into other areas such as Mathematical optimization, Degeneracy (mathematics) and State space. Concepts in Machine learning, as well as related topics in Bayesian inference, are covered in the Bayesian probability research presented in Statistics and Computing.
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 Statistics and Computing (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 Statistics and Computing (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, 7.41% of publications had an unrecognized affiliation. Out of the publications with recognized affiliations, 29.33% were posted by at least one author from the top 10 institutions publishing in the journal. Another 13.33% included authors affiliated with research institutions from the top 11-20 affiliations. Institutions from the 21-50 range included 21.33% of all publications and 36.00% 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.
Arno Solin;Simo Särkkä
(2020)Kris Boudt;Kris Boudt;Kris Boudt;Peter J. Rousseeuw;Steven Vanduffel;Tim Verdonck;Tim Verdonck
(2020)Sergey Dolgov;Karim Anaya-Izquierdo;Colin Fox;Robert Scheichl
(2020)Zheyuan Li;Simon N. Wood
(2020)Ziwen An;Ziwen An;David J. Nott;Christopher C. Drovandi;Christopher C. Drovandi
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