Guanyu Hu
- Economics and Econometrics top 10%
- Artificial Intelligence
- Statistics and Probability top 5%
- Molecular Biology
- Epidemiology
- Co-authors
- Wei Vivian LiAndrew Y. S. ChengMing‐Hui ChenJonathan R. BradleyWeining ShenFred HufferFan YinDipak K. Dey
- Topics
- Bayesian Methods and Mixture Models (14 papers)Spatial and Panel Data Analysis (14 papers)Statistical Methods and Bayesian Inference (12 papers)
- Journals
- Journal of Business and Economic StatisticsBriefings in BioinformaticsJournal of Computational and Graphical Statistics
- Partner nations
- United StatesChinaBrazil
In The Last Decade
Guanyu Hu
29 papers receiving 194 citations
Peers
Comparison fields: 5 of 66
- Economics and Econometrics 69
- Artificial Intelligence 56
- Statistics and Probability 55
- Molecular Biology 40
- Epidemiology 28
Countries citing papers authored by Guanyu Hu
This map shows the geographic impact of Guanyu Hu'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 Guanyu Hu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Guanyu Hu more than expected).
Fields of papers citing papers by Guanyu Hu
This network shows the impact of papers produced by Guanyu Hu. 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 Guanyu Hu. The network helps show where Guanyu Hu may publish in the future.
Co-authorship network of co-authors of Guanyu Hu
This figure shows the co-authorship network connecting the top 25 collaborators of Guanyu Hu. A scholar is included among the top collaborators of Guanyu Hu 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 Guanyu Hu. Guanyu Hu 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 | 2 | |
| 4 | 0 | |
| 5 | 2 | |
| 6 | 9 | |
| 7 | 2 | |
| 8 | 9 | |
| 9 | 3 | |
| 10 | 5 | |
| 11 | 35 | |
| 12 | 1 | |
| 13 | 4 | |
| 14 | 5 | |
| 15 | 9 | |
| 16 | 18 | |
| 17 | 5 | |
| 18 | 1 | |
| 19 | 13 | |
| 20 | Spatial Statistics and Its Applications in Biostatistics and Environmental Statistics | 0 |
About Guanyu Hu
Guanyu Hu is a scholar working on Statistics and Probability, Economics and Econometrics and Artificial Intelligence, having authored 33 papers that have together received 196 indexed citations. Recurring topics across this work include Bayesian Methods and Mixture Models (14 papers), Spatial and Panel Data Analysis (14 papers) and Statistical Methods and Bayesian Inference (12 papers). The work is most often cited by research in Statistics and Probability (55 citations), Modeling and Simulation (12 citations) and Economics and Econometrics (69 citations). Guanyu Hu has collaborated with scholars based in United States, China and Brazil. Frequent co-authors include Wei Vivian Li, Andrew Y. S. Cheng, Ming‐Hui Chen, Jonathan R. Bradley, Weining Shen, Fred Huffer, Fan Yin, Dipak K. Dey, Qingyang Liu and Huiyan Sang. Their work appears in journals such as Journal of Business and Economic Statistics, Briefings in Bioinformatics and Journal of Computational and Graphical 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.