Warren W. Esty
- Statistics and Probability top 5%
- Artificial Intelligence
- Molecular Biology
- Mathematical Physics top 10%
- Ecology
- Topics
- Stochastic processes and statistical mechanics (8 papers)Bayesian Methods and Mixture Models (5 papers)Statistical Methods and Bayesian Inference (4 papers)
- Journals
- Journal of the American Statistical AssociationThe Annals of StatisticsJournal of Statistical Software
- Partner nations
- United States
In The Last Decade
Warren W. Esty
18 papers receiving 286 citations
Peers
Comparison fields: 5 of 121
- Statistics and Probability 102
- Artificial Intelligence 85
- Molecular Biology 52
- Mathematical Physics 50
- Ecology 37
Countries citing papers authored by Warren W. Esty
This map shows the geographic impact of Warren W. Esty'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 Warren W. Esty with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Warren W. Esty more than expected).
Fields of papers citing papers by Warren W. Esty
This network shows the impact of papers produced by Warren W. Esty. 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 Warren W. Esty. The network helps show where Warren W. Esty may publish in the future.
Co-authorship network of co-authors of Warren W. Esty
This figure shows the co-authorship network connecting the top 25 collaborators of Warren W. Esty. A scholar is included among the top collaborators of Warren W. Esty 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 Warren W. Esty. Warren W. Esty is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | Teaching about Inverse Functions. | 1 |
| 2 | 55 | |
| 3 | Mathematical Contexts and the Perception of Meaning in Algebraic Symbols. | 5 |
| 4 | A General-Education Course Emphasizing Mathematical Language and Reasoning. | 4 |
| 5 | Language Concepts of Mathematics. | 22 |
| 6 | 7 | |
| 7 | 2 | |
| 8 | The contribution of surface-silvering to silver content | 2 |
| 9 | 0 | |
| 10 | 0 | |
| 11 | Estimation of the size of a coinage: a survey and comparison of methods | 30 |
| 12 | 4 | |
| 13 | 7 | |
| 14 | Estimating the size of a coinage | 4 |
| 15 | 1 | |
| 16 | 26 | |
| 17 | 9 | |
| 18 | 1 | |
| 19 | 9 | |
| 20 | 9 |
About Warren W. Esty
Warren W. Esty is a scholar working on Statistics and Probability, Mathematical Physics and Architecture, having authored 25 papers that have together received 344 indexed citations. Recurring topics across this work include Stochastic processes and statistical mechanics (8 papers), Bayesian Methods and Mixture Models (5 papers) and Statistical Methods and Bayesian Inference (4 papers). The work is most often cited by research in Statistics and Probability (102 citations), Mathematical Physics (50 citations) and Artificial Intelligence (85 citations). Warren W. Esty has collaborated with scholars based in United States. Frequent co-authors include Jeffrey D. Banfield, Marcus J. Hamilton, David C. Sands and M. J. Faddy. Their work appears in journals such as Journal of the American Statistical Association, The Annals of Statistics and Journal of Statistical Software.
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.