Richard G. Everitt
- Molecular Biology
- Infectious Diseases top 5%
- Clinical Biochemistry top 2%
- Artificial Intelligence top 10%
- Statistics and Probability top 2%
- Co-authors
- Daniel J. WilsonXavier DidelotBernadette YoungDerrick W. CrookTanya GolubchikTim PetoA. Sarah WalkerKevin Cole
- Topics
- Markov Chains and Monte Carlo Methods (7 papers)Bayesian Methods and Mixture Models (5 papers)Target Tracking and Data Fusion in Sensor Networks (4 papers)
- Partner nations
- United KingdomFranceMexico
In The Last Decade
Richard G. Everitt
19 papers receiving 807 citations
Peers
Comparison fields: 5 of 108
- Molecular Biology 266
- Infectious Diseases 245
- Clinical Biochemistry 187
- Artificial Intelligence 171
- Statistics and Probability 144
Countries citing papers authored by Richard G. Everitt
This map shows the geographic impact of Richard G. Everitt'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 G. Everitt with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Richard G. Everitt more than expected).
Fields of papers citing papers by Richard G. Everitt
This network shows the impact of papers produced by Richard G. Everitt. 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 G. Everitt. The network helps show where Richard G. Everitt may publish in the future.
Co-authorship network of co-authors of Richard G. Everitt
This figure shows the co-authorship network connecting the top 25 collaborators of Richard G. Everitt. A scholar is included among the top collaborators of Richard G. Everitt 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 Richard G. Everitt. Richard G. Everitt is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 1 | |
| 2 | 8 | |
| 3 | 8 | |
| 4 | 59 | |
| 5 | 5 | |
| 6 | 3 | |
| 7 | 12 | |
| 8 | 105 | |
| 9 | 234 | |
| 10 | 58 | |
| 11 | 164 | |
| 12 | 4 | |
| 13 | 45 | |
| 14 | 61 | |
| 15 | 3 | |
| 16 | 28 | |
| 17 | Multi-target out-of-sequence data association | 10 |
| 18 | 2 | |
| 19 | 13 |
About Richard G. Everitt
Richard G. Everitt is a scholar working on Statistics and Probability, Artificial Intelligence and Statistics, Probability and Uncertainty, having authored 19 papers that have together received 823 indexed citations. Recurring topics across this work include Markov Chains and Monte Carlo Methods (7 papers), Bayesian Methods and Mixture Models (5 papers) and Target Tracking and Data Fusion in Sensor Networks (4 papers). The work is most often cited by research in Clinical Biochemistry (187 citations), Molecular Medicine (118 citations) and Statistics and Probability (144 citations). Richard G. Everitt has collaborated with scholars based in United Kingdom, France and Mexico. Frequent co-authors include Daniel J. Wilson, Xavier Didelot, Bernadette Young, Derrick W. Crook, Tanya Golubchik, Tim Peto, A. Sarah Walker, Kevin Cole, Martin Llewelyn and M. Morgan. Their work appears in journals such as Nature Communications, PLoS ONE and Journal of Clinical Microbiology.
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.