Stephen Portnoy
- Statistics and Probability top 0.1%
- Artificial Intelligence top 5%
- Statistics, Probability and Uncertainty top 0.5%
- Economics and Econometrics top 2%
- Nature and Landscape Conservation top 5%
- Co-authors
- Roger KoenkerPin NgMary F. WillsonSabrina E. RussoCarol K. AugspurgerXuming HeJana JurečkováDouglas G. Simpson
- Topics
- Statistical Methods and Inference (42 papers)Advanced Statistical Methods and Models (39 papers)Statistical Methods and Bayesian Inference (13 papers)
- Partner nations
- United StatesCzechiaBelgium
In The Last Decade
Stephen Portnoy
78 papers receiving 3.2k citations
Peers
Comparison fields: 5 of 149
- Statistics and Probability 2.2k
- Artificial Intelligence 464
- Statistics, Probability and Uncertainty 441
- Economics and Econometrics 413
- Nature and Landscape Conservation 339
Countries citing papers authored by Stephen Portnoy
This map shows the geographic impact of Stephen Portnoy'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 Stephen Portnoy with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Stephen Portnoy more than expected).
Fields of papers citing papers by Stephen Portnoy
This network shows the impact of papers produced by Stephen Portnoy. 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 Stephen Portnoy. The network helps show where Stephen Portnoy may publish in the future.
Co-authorship network of co-authors of Stephen Portnoy
This figure shows the co-authorship network connecting the top 25 collaborators of Stephen Portnoy. A scholar is included among the top collaborators of Stephen Portnoy 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 Stephen Portnoy. Stephen Portnoy 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 | 6 | |
| 3 | 222 | |
| 4 | 285 | |
| 5 | 2 | |
| 6 | 18 | |
| 7 | 40 | |
| 8 | 28 | |
| 9 | 415 | |
| 10 | 122 | |
| 11 | 76 | |
| 12 | 64 | |
| 13 | 94 | |
| 14 | 8 | |
| 15 | 47 | |
| 16 | 24 | |
| 17 | 5 | |
| 18 | 65 | |
| 19 | 3 | |
| 20 | 5 |
About Stephen Portnoy
Stephen Portnoy is a scholar working on Statistics and Probability, Statistics, Probability and Uncertainty and Numerical Analysis, having authored 81 papers that have together received 3.5k indexed citations. Recurring topics across this work include Statistical Methods and Inference (42 papers), Advanced Statistical Methods and Models (39 papers) and Statistical Methods and Bayesian Inference (13 papers). The work is most often cited by research in Statistics and Probability (2.2k citations), Statistics, Probability and Uncertainty (441 citations) and Finance (332 citations). Stephen Portnoy has collaborated with scholars based in United States, Czechia and Belgium. Frequent co-authors include Roger Koenker, Pin Ng, Mary F. Willson, Sabrina E. Russo, Carol K. Augspurger, Xuming He, Jana Jurečková, Xuming He, Douglas G. Simpson and Christoph Gutenbrünner. Their work appears in journals such as Journal of the American Statistical Association, Ecology and Econometrica.
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.