Nan‐Jung Hsu
- Economics and Econometrics top 5%
- Statistics and Probability top 5%
- Environmental Engineering top 10%
- Finance top 10%
- Artificial Intelligence
- Co-authors
- Ya‐Mei ChangHsin‐Cheng HuangF. Jay BreidtNoel CressieSoumendra N. LahiriMark S. KaiserSheng‐Tsaing TsengDavid M. Theobald
- Topics
- Soil Geostatistics and Mapping (10 papers)Spatial and Panel Data Analysis (8 papers)Financial Risk and Volatility Modeling (6 papers)
- Journals
- SHILAP Revista de lepidopterologíaJournal of the American Statistical AssociationMarine Biology
- Partner nations
- TaiwanUnited StatesItaly
In The Last Decade
Nan‐Jung Hsu
25 papers receiving 421 citations
Peers
Comparison fields: 5 of 93
- Economics and Econometrics 189
- Statistics and Probability 128
- Environmental Engineering 119
- Finance 82
- Artificial Intelligence 63
Countries citing papers authored by Nan‐Jung Hsu
This map shows the geographic impact of Nan‐Jung Hsu'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 Nan‐Jung Hsu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Nan‐Jung Hsu more than expected).
Fields of papers citing papers by Nan‐Jung Hsu
This network shows the impact of papers produced by Nan‐Jung Hsu. 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 Nan‐Jung Hsu. The network helps show where Nan‐Jung Hsu may publish in the future.
Co-authorship network of co-authors of Nan‐Jung Hsu
This figure shows the co-authorship network connecting the top 25 collaborators of Nan‐Jung Hsu. A scholar is included among the top collaborators of Nan‐Jung Hsu 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 Nan‐Jung Hsu. Nan‐Jung Hsu 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 | 0 | |
| 4 | 1 | |
| 5 | 3 | |
| 6 | 19 | |
| 7 | 6 | |
| 8 | 6 | |
| 9 | 4 | |
| 10 | 11 | |
| 11 | 13 | |
| 12 | Semiparametric Estimation of Nonstationary Spatial Covariance Function | 1 |
| 13 | 11 | |
| 14 | 15 | |
| 15 | 1 | |
| 16 | 29 | |
| 17 | 14 | |
| 18 | 69 | |
| 19 | 19 | |
| 20 | 9 |
About Nan‐Jung Hsu
Nan‐Jung Hsu is a scholar working on Statistics and Probability, Environmental Engineering and Finance, having authored 28 papers that have together received 441 indexed citations. Recurring topics across this work include Soil Geostatistics and Mapping (10 papers), Spatial and Panel Data Analysis (8 papers) and Financial Risk and Volatility Modeling (6 papers). The work is most often cited by research in Statistics and Probability (128 citations), Environmental Engineering (119 citations) and Finance (82 citations). Nan‐Jung Hsu has collaborated with scholars based in Taiwan, United States and Italy. Frequent co-authors include Ya‐Mei Chang, Hsin‐Cheng Huang, F. Jay Breidt, Noel Cressie, Soumendra N. Lahiri, Mark S. Kaiser, Sheng‐Tsaing Tseng, David M. Theobald, Randall C. Cutlip and Hans‐Uwe Dahms. Their work appears in journals such as SHILAP Revista de lepidopterología, Journal of the American Statistical Association and Marine Biology.
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.