Dietmar Pfeifer
- Statistics and Probability top 1%
- Finance top 5%
- Management Science and Operations Research top 5%
- Artificial Intelligence top 10%
- Mathematical Physics top 5%
- Co-authors
- Paul DeheuvelsUte Resch‐GengerC. MonteKonstantin BorovkovAngelika HoffmannH. G. O. BeckerD. R. TaubertJ. Hollandt
- Topics
- Probability and Risk Models (14 papers)Bayesian Methods and Mixture Models (12 papers)Stochastic processes and financial applications (10 papers)
- Journals
- Angewandte Chemie International EditionSHILAP Revista de lepidopterologíaAnalytical Chemistry
- Partner nations
- GermanyUnited StatesFrance
In The Last Decade
Dietmar Pfeifer
96 papers receiving 1.2k citations
Peers
Comparison fields: 5 of 129
- Statistics and Probability 373
- Finance 220
- Management Science and Operations Research 215
- Artificial Intelligence 193
- Mathematical Physics 171
Countries citing papers authored by Dietmar Pfeifer
This map shows the geographic impact of Dietmar Pfeifer'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 Dietmar Pfeifer with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Dietmar Pfeifer more than expected).
Fields of papers citing papers by Dietmar Pfeifer
This network shows the impact of papers produced by Dietmar Pfeifer. 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 Dietmar Pfeifer. The network helps show where Dietmar Pfeifer may publish in the future.
Co-authorship network of co-authors of Dietmar Pfeifer
This figure shows the co-authorship network connecting the top 25 collaborators of Dietmar Pfeifer. A scholar is included among the top collaborators of Dietmar Pfeifer 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 Dietmar Pfeifer. Dietmar Pfeifer is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | New copulas based on general partitions-of-unity (part III) — the continuous case | 5 |
| 2 | 2 | |
| 3 | Generating VaR Scenarios under solvency II with product beta distributions | 3 |
| 4 | 7 | |
| 5 | 12 | |
| 6 | 0 | |
| 7 | 26 | |
| 8 | 89 | |
| 9 | 30 | |
| 10 | On Asymptotic Behavior of Weighted Sample Quantiles | 2 |
| 11 | 17 | |
| 12 | 7 | |
| 13 | 29 | |
| 14 | 22 | |
| 15 | 13 | |
| 16 | On the Distance between Mixed Poisson and Poisson Distributions. | 17 |
| 17 | 1 | |
| 18 | 5 | |
| 19 | 10 | |
| 20 | 15 |
About Dietmar Pfeifer
Dietmar Pfeifer is a scholar working on Statistics and Probability, Management Science and Operations Research and Mathematical Physics, having authored 105 papers that have together received 1.3k indexed citations. Recurring topics across this work include Probability and Risk Models (14 papers), Bayesian Methods and Mixture Models (12 papers) and Stochastic processes and financial applications (10 papers). The work is most often cited by research in Statistics and Probability (373 citations), Finance (220 citations) and Mathematical Physics (171 citations). Dietmar Pfeifer has collaborated with scholars based in Germany, United States and France. Frequent co-authors include Paul Deheuvels, Ute Resch‐Genger, C. Monte, Konstantin Borovkov, Angelika Hoffmann, H. G. O. Becker, D. R. Taubert, J. Hollandt, W. Pilz and H. Baumann. Their work appears in journals such as Angewandte Chemie International Edition, SHILAP Revista de lepidopterología and Analytical Chemistry.
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.