Sanying Feng
- Statistics and Probability top 2%
- Economics and Econometrics top 10%
- Artificial Intelligence
- Control and Systems Engineering
- Finance
- Co-authors
- Liugen XueGaorong LiLixing ZhuHeng LianJun ZhangJunhua ZhangTiejun TongYiping Yang
- Topics
- Statistical Methods and Inference (28 papers)Statistical Methods and Bayesian Inference (15 papers)Advanced Statistical Methods and Models (15 papers)
In The Last Decade
Sanying Feng
34 papers receiving 288 citations
Peers
Comparison fields: 5 of 38
- Statistics and Probability 237
- Economics and Econometrics 74
- Artificial Intelligence 36
- Control and Systems Engineering 26
- Finance 26
Countries citing papers authored by Sanying Feng
This map shows the geographic impact of Sanying Feng'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 Sanying Feng with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Sanying Feng more than expected).
Fields of papers citing papers by Sanying Feng
This network shows the impact of papers produced by Sanying Feng. 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 Sanying Feng. The network helps show where Sanying Feng may publish in the future.
Co-authorship network of co-authors of Sanying Feng
This figure shows the co-authorship network connecting the top 25 collaborators of Sanying Feng. A scholar is included among the top collaborators of Sanying Feng 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 Sanying Feng. Sanying Feng 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 | 3 | |
| 4 | 4 | |
| 5 | 20 | |
| 6 | 2 | |
| 7 | 10 | |
| 8 | 1 | |
| 9 | 2 | |
| 10 | 2 | |
| 11 | 4 | |
| 12 | Statistical Inference for Semiparametric Varying Coefficient Partially Linear Model with Missing Data | 1 |
| 13 | 24 | |
| 14 | 19 | |
| 15 | 5 | |
| 16 | 1 | |
| 17 | 16 | |
| 18 | EMPIRICAL LIKELIHOOD INFERENCE OF LINEAR ERRORS-IN-VARIABLES MODELS UNDER VALIDATION DATA FOR MISSING RESPONSE DATA | 1 |
| 19 | 41 | |
| 20 | Maximum Empirical Likelihood Estimator in a Partially Linear Errors-in-variables Regression Model | 2 |
About Sanying Feng
Sanying Feng is a scholar working on Statistics and Probability, Economics and Econometrics and General Economics, Econometrics and Finance, having authored 36 papers that have together received 290 indexed citations. Recurring topics across this work include Statistical Methods and Inference (28 papers), Statistical Methods and Bayesian Inference (15 papers) and Advanced Statistical Methods and Models (15 papers). The work is most often cited by research in Statistics and Probability (237 citations), Economics and Econometrics (74 citations) and Finance (26 citations). Sanying Feng has collaborated with scholars based in China, Hong Kong and Australia. Frequent co-authors include Liugen Xue, Gaorong Li, Lixing Zhu, Heng Lian, Jun Zhang, Junhua Zhang, Tiejun Tong, Yiping Yang, Heng Peng and Yang Zhao. Their work appears in journals such as Economics Letters, Computational Statistics & Data Analysis and Journal of Multivariate Analysis.
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.