| Discipline name | Position | Best Scientists | Publications | D-Index |
|---|---|---|---|---|
| Mathematics | 538 | 8 | 12 | 5 |
AStA Advances in Statistical Analysis primarily focuses on research topics in Statistics, Econometrics, Applied mathematics, Estimator and Mathematical optimization. Statistics and Inference are closely related fields of research discussed in the journal. Sample (statistics) and Bayesian probability are some topics wherein Econometrics research discussed in AStA Advances in Statistical Analysis have an impact.
Markov chain Monte Carlo is a major topic of Bayesian probability research presented in AStA Advances in Statistical Analysis. Applied mathematics research featured in the journal incorporates concerns from various other topics such as Regression and Autoregressive model. AStA Advances in Statistical Analysis explores topics in Estimator which can be helpful for research in disciplines like Nonparametric statistics, Variance (accounting) and Series (mathematics).
It connects the study in Nonparametric statistics with the closely related area of Parametric statistics.
The published articles mostly deal with topics like Econometrics, Statistics, Mathematical optimization, Applied mathematics and Series (mathematics). While the most cited papers focused on Econometrics, they were also able to explore topics like Data mining, Missing data, Categorical variable, Regression analysis and Multivariate normal distribution. In addition to Applied mathematics research, the most cited publications aim to explore topics under Errors-in-variables models, Distribution (mathematics), Laplace's method and Variables.
The journal tackles a plethora of topics, such as Estimator, Econometrics, Applied mathematics, Artificial intelligence and Bayesian probability. In it, researchers investigate the Estimator study as part of research in the field of Statistics. The journal focuses on Econometrics but the discussions also offer insight into other areas such as Multivariate statistics, Contrast (statistics), Rank (computer programming) and Inference.
AStA Advances in Statistical Analysis facilitates discussions on Applied mathematics that incorporate concepts from other fields like Scale (ratio), Random variable, Missing data, Bounded function and Numerical analysis. Issues in Artificial intelligence were discussed, taking into consideration concepts from other disciplines like Nonparametric statistics, Pattern recognition, Machine learning, Receiver operating characteristic and Component (UML). Some problems in Bayesian probability that were presented in it overlapped with concepts under Dimension (vector space), Energy distance, Outcome (game theory) and Covariate.
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 AStA Advances in Statistical Analysis (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 AStA Advances in Statistical Analysis (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, 10.87% were posted by at least one author from the top 10 institutions publishing in the journal. Another 6.52% included authors affiliated with research institutions from the top 11-20 affiliations. Institutions from the 21-50 range included 19.57% of all publications and 63.04% 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.
Sonia Pérez-Fernández;Pablo Martínez-Camblor;Peter Filzmoser;Norberto Corral
(2021)Roger M. Cooke;Harry Joe;Bo Chang
(2020)Jan Pablo Burgard;Domingo Morales;Anna-Lena Wölwer
(2021)Cristine Rauber;Francisco Cribari-Neto;Fábio M. Bayer
(2020)Nadja Klein;Thomas Kneib
(2020)Dankmar Böhning;Patarawan Sangnawakij
(2021)M. P. Wand;J. C. F. Yu
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