Hajime Yamato
- Statistics and Probability top 2%
- Statistical Methods and Inference 15
- Statistical Distribution Estimation and Applications 10
- Advanced Statistical Methods and Models 7
- Statistical Methods and Bayesian Inference 3
- Mathematical Physics top 10%
- Stochastic processes and statistical mechanics 5
- Mathematical Dynamics and Fractals 4
- Finance top 10%
- Financial Risk and Volatility Modeling 5
- Artificial Intelligence top 10%
- Bayesian Methods and Mixture Models 26
- Co-authors
- Masaaki Sibuya
- Journals
- The Annals of Probability (1 paper)Journal of Multivariate Analysis (1 paper)Journal of Statistical Planning and Inference (1 paper)
- Partner nations
- JapanUnited States
In The Last Decade
Hajime Yamato
39 papers receiving 299 citations
Peers
Comparison fields: 5 of 36
- Statistics and Probability 222
- Mathematical Physics 61
- Finance 61
- Artificial Intelligence 192
- Statistics, Probability and Uncertainty 32
Countries citing papers authored by Hajime Yamato
This map shows the geographic impact of Hajime Yamato'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 Hajime Yamato with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Hajime Yamato more than expected).
Fields of papers citing papers by Hajime Yamato
This network shows the impact of papers produced by Hajime Yamato. 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 Hajime Yamato. The network helps show where Hajime Yamato may publish in the future.
Co-authorship network
The 1 scholars most cited alongside Hajime Yamato, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2020 | 2 | |
| 2 | 2015 | 0 | |
| 3 | 2013 | 2 | |
| 4 | 2012 | 1 | |
| 5 | 2003 | 2 | |
| 6 | HIGHER ORDER EFFICIENCY OF LINEAR COMBINATIONS OF U-STATISTICS AS ESTIMATORS OF ESTIMABLE PARAMETERS | 2002 | 2 |
| 7 | INVARIANCE PRINCIPLES FOR A LINEAR COMBINATION OF U-STATISTICS | 2002 | 1 |
| 8 | 2001 | 5 | |
| 9 | 2001 | 4 | |
| 10 | 1999 | 1 | |
| 11 | 1997 | 1 | |
| 12 | 1995 | 2 | |
| 13 | 1993 | 7 | |
| 14 | 1990 | 1 | |
| 15 | 1989 | 2 | |
| 16 | 1986 | 5 | |
| 17 | 1986 | 4 | |
| 18 | ON BEHAVIORS OF MEANS OF DISTRIBUTIONS WITH DIRICHLET PROCESSES | 1980 | 2 |
| 19 | 1977 | 13 | |
| 20 | 1971 | 77 |
About Hajime Yamato
Hajime Yamato is a scholar working on Statistics and Probability, Artificial Intelligence, Mathematical Physics, Finance and Discrete Mathematics and Combinatorics, having authored 42 papers that have together received 329 indexed citations. Recurring topics across this work include Bayesian Methods and Mixture Models (26 papers), Statistical Methods and Inference (15 papers), Statistical Distribution Estimation and Applications (10 papers), Advanced Statistical Methods and Models (7 papers), Financial Risk and Volatility Modeling (5 papers), Stochastic processes and statistical mechanics (5 papers), Mathematical Dynamics and Fractals (4 papers) and Statistical Methods and Bayesian Inference (3 papers). The work is most often cited by research in Statistics and Probability (222 citations), Mathematical Physics (61 citations), Finance (61 citations), Artificial Intelligence (192 citations) and Statistics, Probability and Uncertainty (32 citations). Hajime Yamato has collaborated with scholars based in Japan and United States. Frequent co-authors include Masaaki Sibuya. Their work appears in journals such as The Annals of Probability, Journal of Multivariate Analysis, Journal of Statistical Planning and Inference, Annals of the Institute of Statistical Mathematics and Japan Journal of Industrial and Applied Mathematics.
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.