Wolfgang Polonik
- Statistics and Probability top 1%
- Artificial Intelligence top 5%
- Finance top 10%
- Statistics, Probability and Uncertainty top 5%
- Control and Systems Engineering
- Co-authors
- Qiwei YaoDavid M. MasonEnno MammenPrabir BurmanSamuel NjorogeKrishna V. SubbaraoS. T. KoikeGary E. Vallad
- Topics
- Statistical Methods and Inference (12 papers)Advanced Statistical Methods and Models (10 papers)Bayesian Methods and Mixture Models (8 papers)
- Journals
- Journal of the American Statistical AssociationJournal of EconometricsThe Annals of Statistics
- Partner nations
- United StatesGermanyUnited Kingdom
In The Last Decade
Wolfgang Polonik
24 papers receiving 529 citations
Peers
Comparison fields: 5 of 69
- Statistics and Probability 359
- Artificial Intelligence 218
- Finance 71
- Statistics, Probability and Uncertainty 65
- Control and Systems Engineering 45
Countries citing papers authored by Wolfgang Polonik
This map shows the geographic impact of Wolfgang Polonik'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 Wolfgang Polonik with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Wolfgang Polonik more than expected).
Fields of papers citing papers by Wolfgang Polonik
This network shows the impact of papers produced by Wolfgang Polonik. 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 Wolfgang Polonik. The network helps show where Wolfgang Polonik may publish in the future.
Co-authorship network of co-authors of Wolfgang Polonik
This figure shows the co-authorship network connecting the top 25 collaborators of Wolfgang Polonik. A scholar is included among the top collaborators of Wolfgang Polonik 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 Wolfgang Polonik. Wolfgang Polonik 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 | 0 | |
| 3 | 4 | |
| 4 | 1 | |
| 5 | 0 | |
| 6 | 29 | |
| 7 | 6 | |
| 8 | 28 | |
| 9 | 18 | |
| 10 | 51 | |
| 11 | 22 | |
| 12 | 4 | |
| 13 | 20 | |
| 14 | 15 | |
| 15 | 24 | |
| 16 | 38 | |
| 17 | 19 | |
| 18 | 16 | |
| 19 | 51 | |
| 20 | 27 |
About Wolfgang Polonik
Wolfgang Polonik is a scholar working on Statistics and Probability, Statistics, Probability and Uncertainty and Artificial Intelligence, having authored 27 papers that have together received 567 indexed citations. Recurring topics across this work include Statistical Methods and Inference (12 papers), Advanced Statistical Methods and Models (10 papers) and Bayesian Methods and Mixture Models (8 papers). The work is most often cited by research in Statistics and Probability (359 citations), Statistics, Probability and Uncertainty (65 citations) and Finance (71 citations). Wolfgang Polonik has collaborated with scholars based in United States, Germany and United Kingdom. Frequent co-authors include Qiwei Yao, David M. Mason, Enno Mammen, Prabir Burman, Samuel Njoroge, Krishna V. Subbarao, S. T. Koike, Gary E. Vallad, Seogchan Kang and Mark Bolda. Their work appears in journals such as Journal of the American Statistical Association, Journal of Econometrics and The Annals of Statistics.
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.