R. M. Loynes

82 total papers · 5.5k total citations
61 papers, 3.9k citations indexed

About

R. M. Loynes is a scholar working on Statistics and Probability, Management Science and Operations Research and Finance. According to data from OpenAlex, R. M. Loynes has authored 61 papers receiving a total of 3.9k indexed citations (citations by other indexed papers that have themselves been cited), including 18 papers in Statistics and Probability, 11 papers in Management Science and Operations Research and 7 papers in Finance. Recurrent topics in R. M. Loynes's work include Probability and Risk Models (8 papers), Statistical Methods and Inference (7 papers) and Advanced Statistical Methods and Models (7 papers). R. M. Loynes is often cited by papers focused on Probability and Risk Models (8 papers), Statistical Methods and Inference (7 papers) and Advanced Statistical Methods and Models (7 papers). R. M. Loynes collaborates with scholars based in United Kingdom, Sweden and Canada. R. M. Loynes's co-authors include Peter Hall, C. C. Heyde, A. V. Skorokhod, William Feller, Nedret Billor, Paul D. Minton, Rudolf J. Freund, William J. Hall, David J. Hand and M. J. Crowder and has published in prestigious journals such as Journal of the American Statistical Association, Biometrics and Biometrika.

In The Last Decade

R. M. Loynes

59 papers receiving 3.3k citations

Hit Papers

Martingale Limit Theory a... 1962 2026 1983 2004 1984 1962 500 1000 1.5k

Author Peers

Peers are selected by citation overlap in the author's most active subfields. citations · hero ref

Author Last Decade Papers Cites
R. M. Loynes 1.4k 1.2k 810 763 560 61 3.9k
Paul Dupuis 816 0.6× 1.8k 1.5× 1.1k 1.4× 967 1.3× 859 1.5× 113 5.3k
Kai Lai Chung 1.4k 1.0× 1.3k 1.1× 997 1.2× 2.3k 3.0× 414 0.7× 91 6.4k
Gennady Samorodnitsky 722 0.5× 2.2k 1.8× 1.2k 1.4× 969 1.3× 371 0.7× 192 4.6k
Pierre Brémaud 666 0.5× 903 0.8× 809 1.0× 444 0.6× 870 1.6× 58 3.9k
David Blackwell 1.2k 0.8× 577 0.5× 1.8k 2.2× 498 0.7× 328 0.6× 69 6.6k
S. N. Ethier 1.3k 0.9× 1.7k 1.4× 736 0.9× 2.7k 3.5× 785 1.4× 70 6.1k
Б. В. Гнеденко 612 0.4× 629 0.5× 582 0.7× 833 1.1× 226 0.4× 43 3.3k
R. Liptser 621 0.4× 1.8k 1.5× 523 0.6× 599 0.8× 180 0.3× 81 3.5k
C. C. Heyde 2.5k 1.7× 2.4k 2.0× 1.9k 2.3× 1.7k 2.2× 1.7k 3.0× 187 8.0k
Ν. H. Bingham 1.1k 0.8× 1.8k 1.5× 1.4k 1.8× 2.0k 2.6× 361 0.6× 176 5.0k

Countries citing papers authored by R. M. Loynes

Since Specialization
Citations

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

Fields of papers citing papers by R. M. Loynes

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by R. M. Loynes. 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 R. M. Loynes. The network helps show where R. M. Loynes may publish in the future.

Co-authorship network of co-authors of R. M. Loynes

This figure shows the co-authorship network connecting the top 25 collaborators of R. M. Loynes. A scholar is included among the top collaborators of R. M. Loynes based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with R. M. Loynes. R. M. Loynes is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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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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