1574-1699
Published by: IOS Press
https://www.iospress.nl/journal/model-assisted-statistics-and-applications/
| Discipline name | Position | Best Scientists | Publications | D-Index |
|---|---|---|---|---|
| Mathematics | 708 | 4 | 10 | 3 |
Model Assisted Statistics and Applications is mainly concerned with subjects like Statistics, Econometrics, Estimator, Applied mathematics and Randomized response. The journal facilitated presentations on Statistics research, particularly Mean squared error, Sample (statistics), Sampling (statistics), Regression and Regression analysis. Studies on Econometrics discussed in the journal link to the field of Bivariate analysis.
The main emphasis of the journal is the research on Estimator, emphasizing the topic of Minimum-variance unbiased estimator.
The journal articles are organized to address concerns in the fields of Statistics, Estimator, Randomized response, Econometrics and Randomized Response Technique. Most of the works presented in the journal publications deal with Statistics but they intersect with the subject of Variable (mathematics). The works on Econometrics tackled in the journal papers bring together disciplines like Regression function, Bivariate analysis, Iterated function and Marginal distribution.
The journal facilitates discussions on 2019-20 coronavirus outbreak, Statistics, Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), Estimator and Pandemic. The journal explores topics in 2019-20 coronavirus outbreak which can be helpful for research in disciplines like Prevalence, Beta regression, Demography and Statistical dispersion. The featured works in Mortality rate and Joinpoint regression, which all belong in the domain if Demography, also overlaps with concepts under Running time and Behavioral pattern.
It connects research in Statistics with the related topic of Identification (information). Some problems in Estimator that were presented in Model Assisted Statistics and Applications overlapped with concepts under Generalized extreme value distribution, Logistic regression, Prior probability and Stratified sampling. The close relationship between Econometrics and Probabilistic logic, Seasonality, Autoregressive integrated moving average and Artificial neural network is one of the points of interest dissected in Bounded function research.
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 Model Assisted Statistics and Applications (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 Model Assisted Statistics and Applications (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, 73.91% of publications had an unrecognized affiliation. Out of the publications with recognized affiliations, 0.00% were posted by at least one author from the top 10 institutions publishing in the journal. Another 33.33% included authors affiliated with research institutions from the top 11-20 affiliations. Institutions from the 21-50 range included 16.67% of all publications and 50.00% 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.
Gauss M. Cordeiro;Dalson Figueiredo;Lucas Silva;Edwin M.M. Ortega
(2021)Giovana Oliveira Silva;Gauss M Cordeiro;Edwin Moises Marcos Ortega
(2020)Gladys D.C. Barriga;Dipak K. Dey;Vicente G. Cancho;Adriano K. Suzuki
(2020)Gauss M. Cordeiro;Enivaldo Rocha;Dalson Figueiredo;Antônio Fernandes
(2020)Housila P. Singh;Preeti Patidar
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