S. John
Impact in
- Statistics and Probability top 1%
- Advanced Statistical Methods and Models
- Statistical Methods and Inference
- Statistical Distribution Estimation and Applications
- Statistical Methods and Bayesian Inference
- Random Matrices and Applications
- Finance top 10%
- Financial Risk and Volatility Modeling
Papers in
-
- Advanced Statistical Methods and Models 11
- Statistical Distribution Estimation and Applications 6
- Statistical Methods and Inference 3
- Statistical Methods in Clinical Trials 2
- Statistical Methods and Bayesian Inference 2
-
- Bayesian Methods and Mixture Models 8
- Statistical and Computational Modeling 2
- Journals
- Biometrika (5 papers)Technometrics (3 papers)Annals of the Institute of Statistical Mathematics (2 papers)Journal of the Royal Statistical Society Series B (Statistical Methodology) (2 papers)Journal of Multivariate Analysis (1 paper)
- Partner nations
- AustraliaUnited StatesIndia
In The Last Decade
S. John
20 papers receiving 383 citations
Peers
Comparison fields: 5 of 64
- Statistics and Probability 291
- Finance 65
- Statistics, Probability and Uncertainty 35
- General Economics, Econometrics and Finance 36
- Artificial Intelligence 136
Countries citing papers authored by S. John
This map shows the geographic impact of S. John'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 S. John with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites S. John more than expected).
Fields of papers citing papers by S. John
This network shows the impact of papers produced by S. John. 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 S. John. The network helps show where S. John may publish in the future.
Co-authors
The 2 scholars most cited alongside S. John, 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 | 1971 | 138 | |
| 2 | 1961 | 73 | |
| 3 | 1982 | 67 | |
| 4 | 1983 | 50 | |
| 5 | 1970 | 22 | |
| 6 | 1969 | 15 | |
| 7 | 1961 | 12 | |
| 8 | 1970 | 10 | |
| 9 | 1976 | 9 | |
| 10 | 1968 | 8 | |
| 11 | 1962 | 8 | |
| 12 | 1966 | 3 | |
| 13 | 1973 | 3 | |
| 14 | 1975 | 2 | |
| 15 | 1969 | 2 | |
| 16 | 1970 | 2 | |
| 17 | 1973 | 2 | |
| 18 | 1974 | 2 | |
| 19 | 1974 | 1 | |
| 20 | A table of percentage points of the smallest latent root of a 2 x 2 Wishart matrix | 1969 | 1 |
About S. John
S. John is a scholar working on Statistics and Probability, Artificial Intelligence, Sociology and Political Science, Computer Vision and Pattern Recognition and Computational Theory and Mathematics, having authored 20 papers that have together received 430 indexed citations. Recurring topics across this work include Advanced Statistical Methods and Models (11 papers), Bayesian Methods and Mixture Models (8 papers), Statistical Distribution Estimation and Applications (6 papers), Statistical Methods and Inference (3 papers), Statistical Methods in Clinical Trials (2 papers), Statistical and Computational Modeling (2 papers), Statistical Methods and Bayesian Inference (2 papers) and Spatial and Panel Data Analysis (1 paper). The work is most often cited by research in Statistics and Probability (291 citations), Finance (65 citations), Statistics, Probability and Uncertainty (35 citations), General Economics, Econometrics and Finance (36 citations) and Artificial Intelligence (136 citations). S. John has collaborated with scholars based in Australia, United States and India. Frequent co-authors include Anil K. Bera and David G. Kleinbaum. Their work appears in journals such as Biometrika, Technometrics, Annals of the Institute of Statistical Mathematics, Journal of the Royal Statistical Society Series B (Statistical Methodology) and Journal of Multivariate Analysis.
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.