Electronic Journal of Statistics

1.8k papers and 20.4k indexed citations i.

About

The 1.8k papers published in Electronic Journal of Statistics in the last decades have received a total of 20.4k indexed citations. Papers published in Electronic Journal of Statistics usually cover Statistics and Probability (1.3k papers), Artificial Intelligence (647 papers) and Finance (259 papers) specifically the topics of Statistical Methods and Inference (1.0k papers), Bayesian Methods and Mixture Models (434 papers) and Statistical Methods and Bayesian Inference (418 papers). The most active scholars publishing in Electronic Journal of Statistics are Hemant Ishwaran, Ryan J. Tibshirani, Peter Bühlmann, Aad van der Vaart, Florentina Bunea, Yiyuan She, Elizaveta Levina, Sara A. van de Geer, Pavel N. Krivitsky and Eric P. Xing.

In The Last Decade

Fields of papers published in Electronic Journal of Statistics

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers published in Electronic Journal of Statistics. 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 Electronic Journal of Statistics.

Countries where authors publish in Electronic Journal of Statistics

Since Specialization
Citations

This map shows the geographic impact of research published in Electronic Journal of Statistics. 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 Electronic Journal of Statistics with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Electronic Journal of Statistics more than expected).

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.

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