Michael H. Neumann
- Statistics and Probability top 0.5%
- Finance top 1%
- Economics and Econometrics top 5%
- Artificial Intelligence top 5%
- Computer Vision and Pattern Recognition top 5%
- Co-authors
- Rainer von SachsOla HössjerGeorge SkiadopoulosPaul DoukhanJens‐Peter KreißMarkus ReißJörg PolzehlRainer Dahlhaus
- Topics
- Statistical Methods and Inference (33 papers)Financial Risk and Volatility Modeling (19 papers)Bayesian Methods and Mixture Models (11 papers)
- Partner nations
- GermanyFranceUnited Kingdom
In The Last Decade
Michael H. Neumann
56 papers receiving 1.4k citations
Peers
Comparison fields: 5 of 98
- Statistics and Probability 784
- Finance 623
- Economics and Econometrics 327
- Artificial Intelligence 254
- Computer Vision and Pattern Recognition 191
Countries citing papers authored by Michael H. Neumann
This map shows the geographic impact of Michael H. Neumann'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 Michael H. Neumann with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Michael H. Neumann more than expected).
Fields of papers citing papers by Michael H. Neumann
This network shows the impact of papers produced by Michael H. Neumann. 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 Michael H. Neumann. The network helps show where Michael H. Neumann may publish in the future.
Co-authorship network of co-authors of Michael H. Neumann
This figure shows the co-authorship network connecting the top 25 collaborators of Michael H. Neumann. A scholar is included among the top collaborators of Michael H. Neumann 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 Michael H. Neumann. Michael H. Neumann 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 | 6 | |
| 4 | 6 | |
| 5 | 44 | |
| 6 | 2 | |
| 7 | 39 | |
| 8 | 19 | |
| 9 | DECONVOLUTION FROM NON-STANDARD ERROR DENSITIES UNDER REPLICATED MEASUREMENTS | 7 |
| 10 | Asset Correlations in Turbulent Markets and their Implications on Asset Management | 4 |
| 11 | 67 | |
| 12 | 45 | |
| 13 | 25 | |
| 14 | 28 | |
| 15 | Properties of the Nonparametric Autoregressive Bootstrap | 3 |
| 16 | 15 | |
| 17 | 55 | |
| 18 | 90 | |
| 19 | 24 | |
| 20 | 1 |
About Michael H. Neumann
Michael H. Neumann is a scholar working on Statistics and Probability, Finance and Statistics, Probability and Uncertainty, having authored 58 papers that have together received 1.5k indexed citations. Recurring topics across this work include Statistical Methods and Inference (33 papers), Financial Risk and Volatility Modeling (19 papers) and Bayesian Methods and Mixture Models (11 papers). The work is most often cited by research in Statistics and Probability (784 citations), Finance (623 citations) and General Economics, Econometrics and Finance (177 citations). Michael H. Neumann has collaborated with scholars based in Germany, France and United Kingdom. Frequent co-authors include Rainer von Sachs, Ola Hössjer, George Skiadopoulos, Paul Doukhan, Jens‐Peter Kreiß, Markus Reiß, Jörg Polzehl, Rainer Dahlhaus, J. S. Marron and Iain M. Johnstone. Their work appears in journals such as IEEE Transactions on Information Theory, Biometrika and Journal of Econometrics.
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.