Statistical Science

1.4k papers and 94.1k indexed citations
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About

The 1.4k papers published in Statistical Science in the last decades have received a total of 94.1k indexed citations. Papers published in Statistical Science usually cover Statistics and Probability (623 papers), Artificial Intelligence (274 papers) and Management Science and Operations Research (111 papers) specifically the topics of Statistical Methods and Inference (247 papers), Statistical Methods and Bayesian Inference (215 papers) and Advanced Statistical Methods and Models (158 papers). The most active scholars publishing in Statistical Science are Donald B. Rubin, Andrew Gelman, Elizabeth A. Stuart, Leo Breiman, B. Efron, Trevor Hastie, Robert Tibshirani, Charles J. Geyer, Brian D. Marx and Paul H.C. Eilers.

In The Last Decade

Statistical Science

957 papers receiving 83.5k citations

Fields of papers published in Statistical Science

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers published in Statistical Science. 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 Science.

Countries where authors publish in Statistical Science

Since Specialization
Citations

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