M. L. Eaton
- Statistics and Probability top 2%
- Applied Mathematics top 10%
- Management Science and Operations Research top 10%
- Mathematical Physics
- Computational Theory and Mathematics
- Co-authors
- David E. TylerPersi DiaconisSteffen L. LauritzenBradley EfronLeonard J. SavageMatthew J. SobelIngram OlkinMichael D. Perlman
- Topics
- Bayesian Methods and Mixture Models (5 papers)Statistical Methods and Inference (4 papers)Statistical Methods and Bayesian Inference (2 papers)
- Journals
- Journal of the American Statistical AssociationNeuropharmacologyAmerican Mathematical Monthly
- Partner nations
- United StatesUnited Kingdom
In The Last Decade
M. L. Eaton
10 papers receiving 187 citations
Peers
Comparison fields: 5 of 65
- Statistics and Probability 137
- Applied Mathematics 51
- Management Science and Operations Research 47
- Mathematical Physics 33
- Computational Theory and Mathematics 30
Countries citing papers authored by M. L. Eaton
This map shows the geographic impact of M. L. Eaton'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 M. L. Eaton with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites M. L. Eaton more than expected).
Fields of papers citing papers by M. L. Eaton
This network shows the impact of papers produced by M. L. Eaton. 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 M. L. Eaton. The network helps show where M. L. Eaton may publish in the future.
Co-authorship network of co-authors of M. L. Eaton
This figure shows the co-authorship network connecting the top 25 collaborators of M. L. Eaton. A scholar is included among the top collaborators of M. L. Eaton 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 M. L. Eaton. M. L. Eaton is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 0 | |
| 2 | 2 | |
| 3 | 0 | |
| 4 | 50 | |
| 5 | Finite de Finetti theorems in linear models and multivariate analysis | 45 |
| 6 | 3 | |
| 7 | 2 | |
| 8 | 1 | |
| 9 | 12 | |
| 10 | Lectures on topics in probability inequalities | 34 |
| 11 | Inequalitites on the probability content of convex regions for elliptically contoured distributions | 48 |
| 12 | 23 | |
| 13 | 13 |
About M. L. Eaton
M. L. Eaton is a scholar working on Statistics and Probability, Artificial Intelligence and Computer Science Applications, having authored 13 papers that have together received 233 indexed citations. Recurring topics across this work include Bayesian Methods and Mixture Models (5 papers), Statistical Methods and Inference (4 papers) and Statistical Methods and Bayesian Inference (2 papers). The work is most often cited by research in Statistics and Probability (137 citations), Discrete Mathematics and Combinatorics (18 citations) and Applied Mathematics (51 citations). M. L. Eaton has collaborated with scholars based in United States and United Kingdom. Frequent co-authors include David E. Tyler, Persi Diaconis, Steffen L. Lauritzen, Bradley Efron, Leonard J. Savage, Matthew J. Sobel, Ingram Olkin, Michael D. Perlman, R. J. Senter and Y. L. Tong. Their work appears in journals such as Journal of the American Statistical Association, Neuropharmacology and American Mathematical Monthly.
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.