Countries where authors publish in Statistical Modelling
Since Specialization
Citations
This map shows the geographic impact of research published in Statistical Modelling. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by papers published in Statistical Modelling with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Statistical Modelling more than expected).
Fields of papers published in Statistical Modelling
This network shows the impact of papers published in Statistical Modelling. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers published in Statistical Modelling.
About Statistical Modelling
The 550 papers published in Statistical Modelling in the last decades have received a total of 11.2k indexed citations . Papers published in Statistical Modelling usually cover Statistics and Probability (240 papers), Economics and Econometrics (38 papers), Artificial Intelligence (46 papers), Finance (11 papers) and Demography (8 papers) specifically the topics of Statistical Methods and Bayesian Inference (121 papers), Statistical Methods and Inference (49 papers), Bayesian Methods and Mixture Models (42 papers), Statistical Distribution Estimation and Applications (26 papers), Spatial and Panel Data Analysis (26 papers), Advanced Statistical Methods and Models (23 papers), Sports Analytics and Performance (11 papers) and Financial Risk and Volatility Modeling (9 papers). The most active scholars publishing in Statistical Modelling are Paul H.C. Eilers, Alan Agresti, Thomas Kneib, Maŕıa Durbán, Iain D. Currie, Bruce D. McCullough, Robert L. Kieschnick, Harvey Goldstein, Elisabeth Waldmann and Yongyi Min.
Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive
bibliographic database. While OpenAlex provides broad and valuable coverage of the global
research landscape, it—like all bibliographic datasets—has inherent limitations. These include
incomplete records, variations in author disambiguation, differences in journal indexing, and
delays in data updates. As a result, some metrics and network relationships displayed in
Rankless may not fully capture the entirety of a scholar's output or impact.