Yasuko Chikuse
Impact in
- Statistics and Probability top 2%
- Advanced Statistical Methods and Models
- Statistical Methods and Inference
- Random Matrices and Applications
- Statistical Distribution Estimation and Applications
- Applied Mathematics top 5%
- Mathematical functions and polynomials
Papers in
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- Advanced Statistical Methods and Models 13
- Random Matrices and Applications 9
- Statistical Methods and Inference 6
- Statistical Methods and Bayesian Inference 2
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- Bayesian Methods and Mixture Models 8
- Neural Networks and Applications 2
- Co-authors
- A. W. Davis (2 shared papers)Robb J. Muirhead (2 shared papers)G. S. Watson (1 shared paper)Peter E. Jupp (1 shared paper)
- Journals
- Journal of Multivariate Analysis (11 papers)Linear Algebra and its Applications (7 papers)Annals of the Institute of Statistical Mathematics (4 papers)Econometric Theory (3 papers)The Annals of Statistics (2 papers)
- Partner nations
- JapanCanadaUnited States
In The Last Decade
Yasuko Chikuse
32 papers receiving 478 citations
Peers
Comparison fields: 5 of 69
- Statistics and Probability 221
- Applied Mathematics 80
- Geometry and Topology 62
- Computational Mathematics 4
- General Economics, Econometrics and Finance 40
Countries citing papers authored by Yasuko Chikuse
This map shows the geographic impact of Yasuko Chikuse'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 Yasuko Chikuse with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Yasuko Chikuse more than expected).
Fields of papers citing papers by Yasuko Chikuse
This network shows the impact of papers produced by Yasuko Chikuse. 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 Yasuko Chikuse. The network helps show where Yasuko Chikuse may publish in the future.
Co-authors
The 4 scholars most cited alongside Yasuko Chikuse, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 32 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2003 | 248 | |
| 2 | 1986 | 26 | |
| 3 | 1990 | 23 | |
| 4 | 1986 | 20 | |
| 5 | 1981 | 17 | |
| 6 | 1975 | 17 | |
| 7 | 1987 | 15 | |
| 8 | 1990 | 12 | |
| 9 | 1992 | 10 | |
| 10 | 1998 | 10 | |
| 11 | 1976 | 10 | |
| 12 | 2006 | 10 | |
| 13 | 1986 | 9 | |
| 14 | 1976 | 9 | |
| 15 | 1991 | 8 | |
| 16 | 1995 | 8 | |
| 17 | 1990 | 8 | |
| 18 | 2003 | 7 | |
| 19 | 2003 | 6 | |
| 20 | 1992 | 5 |
About Yasuko Chikuse
Yasuko Chikuse is a scholar working on Statistics and Probability, Artificial Intelligence, Applied Mathematics, Geometry and Topology and Statistical and Nonlinear Physics, having authored 32 papers that have together received 510 indexed citations. Recurring topics across this work include Advanced Statistical Methods and Models (13 papers), Random Matrices and Applications (9 papers), Bayesian Methods and Mixture Models (8 papers), Statistical Methods and Inference (6 papers), Mathematical functions and polynomials (5 papers), Morphological variations and asymmetry (4 papers), Statistical Methods and Bayesian Inference (2 papers) and Neural Networks and Applications (2 papers). The work is most often cited by research in Statistics and Probability (221 citations), Applied Mathematics (80 citations), Geometry and Topology (62 citations), Computational Mathematics (4 citations) and General Economics, Econometrics and Finance (40 citations). Yasuko Chikuse has collaborated with scholars based in Japan, Canada and United States. Frequent co-authors include A. W. Davis, Robb J. Muirhead, G. S. Watson and Peter E. Jupp. Their work appears in journals such as Journal of Multivariate Analysis, Linear Algebra and its Applications, Annals of the Institute of Statistical Mathematics, Econometric Theory 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.