Wai‐Yin Poon
- Statistics and Probability top 0.5%
- Management Science and Operations Research top 2%
- Artificial Intelligence top 10%
- Economics and Econometrics top 10%
- Food Science top 10%
- Co-authors
- Sik‐Yum LeePeter M. BentlerYat Sun PoonMan‐Lai TangHenry S. KingdonKwok LeungSiu Hung CheungNiansheng Tang
- Topics
- Statistical Methods and Bayesian Inference (39 papers)Advanced Statistical Methods and Models (39 papers)Statistical Methods and Inference (17 papers)
- Cited by
- Statistics and ProbabilityManagement Science and Operations ResearchStatistics, Probability and Uncertainty
- Journals
- Statistics in MedicineJournal of the Royal Statistical Society Series B (Statistical Methodology)Psychometrika
- Partner nations
- Hong KongChinaUnited States
In The Last Decade
Wai‐Yin Poon
80 papers receiving 1.3k citations
Peers
Comparison fields: 5 of 134
- Statistics and Probability 761
- Management Science and Operations Research 271
- Artificial Intelligence 170
- Economics and Econometrics 108
- Food Science 99
Countries citing papers authored by Wai‐Yin Poon
This map shows the geographic impact of Wai‐Yin Poon'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 Wai‐Yin Poon with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Wai‐Yin Poon more than expected).
Fields of papers citing papers by Wai‐Yin Poon
This network shows the impact of papers produced by Wai‐Yin Poon. 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 Wai‐Yin Poon. The network helps show where Wai‐Yin Poon may publish in the future.
Co-authorship network of co-authors of Wai‐Yin Poon
This figure shows the co-authorship network connecting the top 25 collaborators of Wai‐Yin Poon. A scholar is included among the top collaborators of Wai‐Yin Poon 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 Wai‐Yin Poon. Wai‐Yin Poon 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 | 0 | |
| 3 | 4 | |
| 4 | 7 | |
| 5 | 17 | |
| 6 | 3 | |
| 7 | 21 | |
| 8 | 15 | |
| 9 | 2 | |
| 10 | 4 | |
| 11 | 7 | |
| 12 | 22 | |
| 13 | 2 | |
| 14 | 16 | |
| 15 | 7 | |
| 16 | 7 | |
| 17 | 3 | |
| 18 | 194 | |
| 19 | 5 | |
| 20 | Errata for Maximum Likelihood Estimation of Multivariate Polyserial and Polychoric Correlation Coefficients. | 0 |
About Wai‐Yin Poon
Wai‐Yin Poon is a scholar working on Statistics and Probability, Computational Mathematics and Statistics, Probability and Uncertainty, having authored 85 papers that have together received 1.3k indexed citations. Recurring topics across this work include Statistical Methods and Bayesian Inference (39 papers), Advanced Statistical Methods and Models (39 papers) and Statistical Methods and Inference (17 papers). The work is most often cited by research in Statistics and Probability (761 citations), Management Science and Operations Research (271 citations) and Statistics, Probability and Uncertainty (97 citations). Wai‐Yin Poon has collaborated with scholars based in Hong Kong, China and United States. Frequent co-authors include Sik‐Yum Lee, Peter M. Bentler, Yat Sun Poon, Man‐Lai Tang, Henry S. Kingdon, Kwok Leung, Siu Hung Cheung, Niansheng Tang, Hoi Shan Kwan and Paul Lam. Their work appears in journals such as Statistics in Medicine, Journal of the Royal Statistical Society Series B (Statistical Methodology) and Psychometrika.
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.