Nengxiang Ling
- Statistics and Probability top 1%
- Artificial Intelligence top 10%
- Management Science and Operations Research top 5%
- Finance top 10%
- Control and Systems Engineering
- Co-authors
- Philippe VieuShuhe HuWenzhi YangGermán AneirosXuejun WangYuehua WuHui DingYi Wu
- Topics
- Statistical Methods and Inference (28 papers)Bayesian Methods and Mixture Models (14 papers)Advanced Statistical Methods and Models (8 papers)
In The Last Decade
Nengxiang Ling
32 papers receiving 445 citations
Peers
Comparison fields: 5 of 51
- Statistics and Probability 374
- Artificial Intelligence 183
- Management Science and Operations Research 127
- Finance 72
- Control and Systems Engineering 35
Countries citing papers authored by Nengxiang Ling
This map shows the geographic impact of Nengxiang Ling'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 Nengxiang Ling with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Nengxiang Ling more than expected).
Fields of papers citing papers by Nengxiang Ling
This network shows the impact of papers produced by Nengxiang Ling. 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 Nengxiang Ling. The network helps show where Nengxiang Ling may publish in the future.
Co-authorship network of co-authors of Nengxiang Ling
This figure shows the co-authorship network connecting the top 25 collaborators of Nengxiang Ling. A scholar is included among the top collaborators of Nengxiang Ling 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 Nengxiang Ling. Nengxiang Ling is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 1 | |
| 2 | 0 | |
| 3 | 0 | |
| 4 | 4 | |
| 5 | 3 | |
| 6 | 2 | |
| 7 | 19 | |
| 8 | 14 | |
| 9 | 27 | |
| 10 | Convergence Rates for Empirical Bayes Tests for the Shape Parameter of Lomax Distribution Family | 1 |
| 11 | 5 | |
| 12 | 16 | |
| 13 | 9 | |
| 14 | 2 | |
| 15 | 16 | |
| 16 | 22 | |
| 17 | Strong consistency of wavelet estimation in the semiparametric regression model | 1 |
| 18 | 38 | |
| 19 | 4 | |
| 20 | Strong Convergence and Its Rate of Modified Partitioning Estimation for Nonparametric Regression Function under Dependence Samples | 1 |
About Nengxiang Ling
Nengxiang Ling is a scholar working on Statistics and Probability, Finance and Management Science and Operations Research, having authored 36 papers that have together received 453 indexed citations. Recurring topics across this work include Statistical Methods and Inference (28 papers), Bayesian Methods and Mixture Models (14 papers) and Advanced Statistical Methods and Models (8 papers). The work is most often cited by research in Statistics and Probability (374 citations), Management Science and Operations Research (127 citations) and Finance (72 citations). Nengxiang Ling has collaborated with scholars based in China, France and Spain. Frequent co-authors include Philippe Vieu, Shuhe Hu, Wenzhi Yang, Germán Aneiros, Xuejun Wang, Xuejun Wang, Yuehua Wu, Xuejun Wang, Hui Ding and Yi Wu. Their work appears in journals such as Journal of the Royal Statistical Society Series B (Statistical Methodology), Journal of Multivariate Analysis and Journal of Statistical Planning and Inference.
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.