Vladimir Spokoiny
- Statistics and Probability top 0.2%
- Artificial Intelligence top 2%
- Finance top 2%
- Computer Vision and Pattern Recognition top 5%
- Economics and Econometrics top 5%
- Co-authors
- Yurii NesterovJörg PolzehlJoël L. HorowitzOleg LepskiAnatoli JuditskyMarian HristacheWolfgang Karl HärdleLutz Dümbgen
- Topics
- Statistical Methods and Inference (46 papers)Advanced Statistical Methods and Models (18 papers)Financial Risk and Volatility Modeling (15 papers)
- Partner nations
- GermanyRussiaUnited States
In The Last Decade
Vladimir Spokoiny
103 papers receiving 2.5k citations
Hit Papers
Peers
Comparison fields: 5 of 127
- Statistics and Probability 1.3k
- Artificial Intelligence 679
- Finance 471
- Computer Vision and Pattern Recognition 334
- Economics and Econometrics 314
Countries citing papers authored by Vladimir Spokoiny
This map shows the geographic impact of Vladimir Spokoiny'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 Vladimir Spokoiny with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Vladimir Spokoiny more than expected).
Fields of papers citing papers by Vladimir Spokoiny
This network shows the impact of papers produced by Vladimir Spokoiny. 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 Vladimir Spokoiny. The network helps show where Vladimir Spokoiny may publish in the future.
Co-authorship network of co-authors of Vladimir Spokoiny
This figure shows the co-authorship network connecting the top 25 collaborators of Vladimir Spokoiny. A scholar is included among the top collaborators of Vladimir Spokoiny 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 Vladimir Spokoiny. Vladimir Spokoiny 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 | 1 | |
| 3 | 3 | |
| 4 | 3 | |
| 5 | 1 | |
| 6 | 3 | |
| 7 | 13 | |
| 8 | Convergence of an alternating maximization procedure | 7 |
| 9 | Roughness penalty, Wilks Phenomenon, and Bernstein - von Mises Theorem | 1 |
| 10 | Wilks Theorem for penalized maximum likelihood estimators | 0 |
| 11 | 2 | |
| 12 | Time Inhomogeneous Multiple Volatility Modeling | 1 |
| 13 | 0 | |
| 14 | Non-Gaussian Component Analysis: a Semi-parametric Framework for Linear Dimension Reduction | 4 |
| 15 | When did the 2001 recession really end? | 1 |
| 16 | Freidlin-Wentzell type large deviations for smooth processes | 5 |
| 17 | 14 | |
| 18 | 32 | |
| 19 | 14 | |
| 20 | 3 |
About Vladimir Spokoiny
Vladimir Spokoiny is a scholar working on Statistics and Probability, Finance and Applied Mathematics, having authored 107 papers that have together received 2.7k indexed citations. Recurring topics across this work include Statistical Methods and Inference (46 papers), Advanced Statistical Methods and Models (18 papers) and Financial Risk and Volatility Modeling (15 papers). The work is most often cited by research in Statistics and Probability (1.3k citations), Finance (471 citations) and Statistics, Probability and Uncertainty (174 citations). Vladimir Spokoiny has collaborated with scholars based in Germany, Russia and United States. Frequent co-authors include Yurii Nesterov, Jörg Polzehl, Joël L. Horowitz, Oleg Lepski, Anatoli Juditsky, Marian Hristache, Wolfgang Karl Härdle, Lutz Dümbgen, Enno Mammen and Albert N. Shiryaev. Their work appears in journals such as Journal of the American Statistical Association, NeuroImage 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.