Tak K. Mak
- Statistics and Probability top 1%
- Finance top 5%
- Economics and Econometrics top 5%
- General Economics, Econometrics and Finance top 5%
- Artificial Intelligence top 10%
- Co-authors
- Anthony Y. C. KukLai K. ChanHeung Wong
- Topics
- Advanced Statistical Methods and Models (18 papers)Statistical Methods and Bayesian Inference (11 papers)Optimal Experimental Design Methods (7 papers)
- Journals
- BiometrikaJournal of the Royal Statistical Society Series B (Statistical Methodology)Journal of the Royal Statistical Society Series C (Applied Statistics)
- Partner nations
- CanadaHong KongUnited States
In The Last Decade
Tak K. Mak
30 papers receiving 543 citations
Peers
Comparison fields: 5 of 74
- Statistics and Probability 389
- Finance 194
- Economics and Econometrics 159
- General Economics, Econometrics and Finance 99
- Artificial Intelligence 95
Countries citing papers authored by Tak K. Mak
This map shows the geographic impact of Tak K. Mak'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 Tak K. Mak with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Tak K. Mak more than expected).
Fields of papers citing papers by Tak K. Mak
This network shows the impact of papers produced by Tak K. Mak. 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 Tak K. Mak. The network helps show where Tak K. Mak may publish in the future.
Co-authorship network of co-authors of Tak K. Mak
This figure shows the co-authorship network connecting the top 25 collaborators of Tak K. Mak. A scholar is included among the top collaborators of Tak K. Mak 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 Tak K. Mak. Tak K. Mak is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | Factor Analysis and Methods of Supplier Selection | 6 |
| 2 | 0 | |
| 3 | 0 | |
| 4 | 3 | |
| 5 | 4 | |
| 6 | 5 | |
| 7 | 22 | |
| 8 | 0 | |
| 9 | 23 | |
| 10 | 15 | |
| 11 | 63 | |
| 12 | 2 | |
| 13 | 3 | |
| 14 | 13 | |
| 15 | 1 | |
| 16 | Maximum likelihood estimation in multivariate structural relationships | 6 |
| 17 | 8 | |
| 18 | 4 | |
| 19 | 18 | |
| 20 | 28 |
About Tak K. Mak
Tak K. Mak is a scholar working on Statistics and Probability, Statistics, Probability and Uncertainty and Management Science and Operations Research, having authored 35 papers that have together received 596 indexed citations. Recurring topics across this work include Advanced Statistical Methods and Models (18 papers), Statistical Methods and Bayesian Inference (11 papers) and Optimal Experimental Design Methods (7 papers). The work is most often cited by research in Statistics and Probability (389 citations), Finance (194 citations) and Statistics, Probability and Uncertainty (89 citations). Tak K. Mak has collaborated with scholars based in Canada, Hong Kong and United States. Frequent co-authors include Anthony Y. C. Kuk, Lai K. Chan and Heung Wong. Their work appears in journals such as Biometrika, Journal of the Royal Statistical Society Series B (Statistical Methodology) and Journal of the Royal Statistical Society Series C (Applied 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.