Richard M. Royall

71 papers and 5.7k indexed citations i.

About

Richard M. Royall is a scholar working on Statistics and Probability, Artificial Intelligence and Surgery. According to data from OpenAlex, Richard M. Royall has authored 71 papers receiving a total of 5.7k indexed citations (citations by other indexed papers that have themselves been cited), including 32 papers in Statistics and Probability, 17 papers in Artificial Intelligence and 6 papers in Surgery. Recurrent topics in Richard M. Royall’s work include Statistical Methods and Bayesian Inference (18 papers), Survey Sampling and Estimation Techniques (17 papers) and Bayesian Methods and Mixture Models (13 papers). Richard M. Royall is often cited by papers focused on Statistical Methods and Bayesian Inference (18 papers), Survey Sampling and Estimation Techniques (17 papers) and Bayesian Methods and Mixture Models (13 papers). Richard M. Royall collaborates with scholars based in United States, Taiwan and Canada. Richard M. Royall's co-authors include Jaxk Reeves, William G. Cumberland, Jay Herson, Thomas M. Brushart, William R. Bell, Guy M. McKhann, Louis M. Borowicz, Maura A. Grega, Steven N. Goodman and Alan H. Dorfman and has published in prestigious journals such as New England Journal of Medicine, JAMA and Journal of Neuroscience.

In The Last Decade

Co-authorship network of co-authors of Richard M. Royall i

Fields of papers citing papers by Richard M. Royall

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Richard M. Royall. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Richard M. Royall. The network helps show where Richard M. Royall may publish in the future.

Countries citing papers authored by Richard M. Royall

Since Specialization
Citations

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