1549-5787
Published by: Institute of Mathematical Statistics
https://imstat.org/journals-and-publications/probability-surveys/
| Discipline name | Position | Best Scientists | Publications | D-Index |
|---|---|---|---|---|
| Mathematics | 475 | 8 | 8 | 6 |
Probability Surveys mainly tackles studies in Discrete mathematics, Mathematical analysis, Pure mathematics, Random variable and Brownian motion. In addition to Discrete mathematics research, Probability Surveys aims to explore topics under Stochastic process, Mathematical proof and Calculus. It explores topics in Mathematical proof which can be helpful for research in disciplines like Martingale (probability theory), Queueing theory and Random walk, Self-avoiding walk.
The featured works in Hilbert space and Stochastic partial differential equation, which all belong in the domain if Mathematical analysis, also overlaps with concepts under Jump, Invariant measure and Geometric Brownian motion. The studies in Pure mathematics featured incorporate elements of Random matrix, Large deviations theory and Lévy process. The studies on Random variable discussed can also contribute to research in the domains of Combinatorics, Type (model theory), Central limit theorem, Mathematical optimization and Applied mathematics.
Point process and Markov chain are some topics wherein Central limit theorem research discussed in Probability Surveys have an impact. While it focused on Applied mathematics, it was also able to explore topics like Balance equation, Additive Markov chain and Discrete time and continuous time. The journal covers research in Brownian motion, particularly Fractional Brownian motion and how they are related with concepts in Brownian excursion and Diffusion process.
The published papers are organized to reinforce research efforts on Discrete mathematics, Mathematical analysis, Applied mathematics, Markov chain and Random matrix. While work presented in the journal publications provide substantial information on Discrete mathematics, it also covers topics in Optimal stopping, Stochastic process, Mathematical proof and Degree (graph theory). Issues in Applied mathematics were discussed in the most cited articles, taking into consideration concepts from other disciplines like Markov chain mixing time, Mathematical optimization, Markov model and Differential equation.
The journal mostly deals with topics like Lévy process, Series (mathematics), Algebra, Random matrix and Markov process. The research on Lévy process featured in the journal combines topics in other fields like Truncation and Representation (mathematics). The study of Mathematical analysis serves as the foundation of the Series (mathematics) research discussed in the journal.
The research on Markov process tackled can also make contributions to studies in the areas of Variety (cybernetics), Pointwise, Entropy (information theory) and Markov chain. The journal facilitates the exploration of Process (engineering) in relation to the other disciplines, such as Algorithm and Cover (topology).
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 Probability Surveys (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 Probability Surveys (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, 33.33% of publications had an unrecognized affiliation. Out of the publications with recognized affiliations, 25.00% were posted by at least one author from the top 10 institutions publishing in the journal. Another 50.00% included authors affiliated with research institutions from the top 11-20 affiliations. Institutions from the 21-50 range included 0.00% of all publications and 25.00% 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.
Van H. Vu
(2021)Gusztáv Morvai;Benjamin Weiss
(2021)Alexander Goldenshluger;Yaakov Malinovsky;Assaf Zeevi
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