Weixing Song
- Statistics and Probability top 2%
- Artificial Intelligence top 10%
- Statistics, Probability and Uncertainty top 5%
- Molecular Biology
- Biochemistry
- Co-authors
- Hira L. KoulWeixin YaoJianhong ShiJianteng XuDavina RhodesBenjamin B. KatzJohn M. TomichXiaoyu Su
- Topics
- Statistical Methods and Inference (33 papers)Advanced Statistical Methods and Models (26 papers)Statistical Methods and Bayesian Inference (14 papers)
- Partner nations
- United StatesChinaAustralia
In The Last Decade
Weixing Song
47 papers receiving 407 citations
Peers
Comparison fields: 5 of 94
- Statistics and Probability 224
- Artificial Intelligence 99
- Statistics, Probability and Uncertainty 43
- Molecular Biology 40
- Biochemistry 34
Countries citing papers authored by Weixing Song
This map shows the geographic impact of Weixing Song'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 Weixing Song with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Weixing Song more than expected).
Fields of papers citing papers by Weixing Song
This network shows the impact of papers produced by Weixing Song. 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 Weixing Song. The network helps show where Weixing Song may publish in the future.
Co-authorship network of co-authors of Weixing Song
This figure shows the co-authorship network connecting the top 25 collaborators of Weixing Song. A scholar is included among the top collaborators of Weixing Song 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 Weixing Song. Weixing Song 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 | 1 | |
| 3 | 22 | |
| 4 | 0 | |
| 5 | 0 | |
| 6 | 2 | |
| 7 | 2 | |
| 8 | 8 | |
| 9 | 49 | |
| 10 | 1 | |
| 11 | 5 | |
| 12 | 7 | |
| 13 | A class of goodness-of-fit tests in linear errors-in-variables model | 2 |
| 14 | 2 | |
| 15 | 1 | |
| 16 | 3 | |
| 17 | MODEL CHECKING IN PARTIAL LINEAR REGRESSION MODELS WITH BERKSON MEASUREMENT ERRORS | 8 |
| 18 | 6 | |
| 19 | 12 | |
| 20 | 41 |
About Weixing Song
Weixing Song is a scholar working on Statistics and Probability, Statistics, Probability and Uncertainty and Numerical Analysis, having authored 51 papers that have together received 419 indexed citations. Recurring topics across this work include Statistical Methods and Inference (33 papers), Advanced Statistical Methods and Models (26 papers) and Statistical Methods and Bayesian Inference (14 papers). The work is most often cited by research in Statistics and Probability (224 citations), Statistics, Probability and Uncertainty (43 citations) and Biochemistry (34 citations). Weixing Song has collaborated with scholars based in United States, China and Australia. Frequent co-authors include Hira L. Koul, Weixin Yao, Jianhong Shi, Jianteng Xu, Davina Rhodes, Benjamin B. Katz, John M. Tomich, Xiaoyu Su, Yanting Shen and Weiqun Wang. Their work appears in journals such as Journal of Hazardous Materials, Food Chemistry and The FASEB Journal.
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.