Yuehua Wu
- Statistics and Probability top 0.5%
- Statistical Methods and Inference 54
- Advanced Statistical Methods and Models 31
- Statistical Methods and Bayesian Inference 9
- Statistical Distribution Estimation and Applications 8
- Global and Planetary Change top 5%
- Atmospheric Science top 5%
- Finance top 5%
- Financial Risk and Volatility Modeling 8
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- Control Systems and Identification 13
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- Bayesian Methods and Mixture Models 13
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- Statistical and numerical algorithms 8
- Co-authors
- Xiaolan L. WangQiuzi Han WenZhidong BaiC. Radhakrishna RaoHanfeng ChenYang FengQiang PuR. Ranga Rao
- Journals
- New England Journal of Medicine (1 paper)Proceedings of the National Academy of Sciences (6 papers)SHILAP Revista de lepidopterología (1 paper)
- Partner nations
- CanadaChinaUnited States
In The Last Decade
Yuehua Wu
105 papers receiving 1.7k citations
Peers
Comparison fields: 5 of 153
- Statistics and Probability 532
- Global and Planetary Change 510
- Atmospheric Science 363
- Finance 148
- Management Science and Operations Research 137
Countries citing papers authored by Yuehua Wu
This map shows the geographic impact of Yuehua Wu'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 Yuehua Wu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Yuehua Wu more than expected).
Fields of papers citing papers by Yuehua Wu
This network shows the impact of papers produced by Yuehua Wu. 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 Yuehua Wu. The network helps show where Yuehua Wu may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Yuehua Wu, 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 | 2024 | 4 | |
| 2 | 2024 | 1 | |
| 3 | 2023 | 4 | |
| 4 | 2023 | 2 | |
| 5 | 2023 | 2 | |
| 6 | 2023 | 0 | |
| 7 | 2023 | 0 | |
| 8 | 2023 | 0 | |
| 9 | 2020 | 33 | |
| 10 | 2020 | 3 | |
| 11 | 2020 | 5 | |
| 12 | 2018 | 7 | |
| 13 | 2017 | 20 | |
| 14 | 2015 | 17 | |
| 15 | 2014 | 9 | |
| 16 | Data Fusion Using Weighted Likelihood | 2012 | 4 |
| 17 | Estimation and Selection in Regression Clustering | 2011 | 2 |
| 18 | 2011 | 4 | |
| 19 | STRONG LIMIT THEOREMS ON MODEL SELECTION IN GENERALIZED LINEAR REGRESSION WITH BINOMIAL RESPONSES | 2006 | 4 |
| 20 | 1989 | 7 |
About Yuehua Wu
Yuehua Wu is a scholar working on Statistics and Probability, Finance and Statistics, Probability and Uncertainty, having authored 125 papers that have together received 1.7k indexed citations. Recurring topics across this work include Statistical Methods and Inference (54 papers), Advanced Statistical Methods and Models (31 papers), Control Systems and Identification (13 papers), Bayesian Methods and Mixture Models (13 papers), Statistical Methods and Bayesian Inference (9 papers), Statistical and numerical algorithms (8 papers), Statistical Distribution Estimation and Applications (8 papers) and Financial Risk and Volatility Modeling (8 papers). The work is most often cited by research in Statistics and Probability (532 citations), Global and Planetary Change (510 citations) and Atmospheric Science (363 citations). Yuehua Wu has collaborated with scholars based in Canada, China and United States. Frequent co-authors include Xiaolan L. Wang, Qiuzi Han Wen, Zhidong Bai, C. Radhakrishna Rao, Hanfeng Chen, Yang Feng, Qiang Pu, R. Ranga Rao, Xiaoping Shi and Jin Zhang. Their work appears in journals such as New England Journal of Medicine, Proceedings of the National Academy of Sciences and SHILAP Revista de lepidopterología.
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.