James R. Schott
- Statistics and Probability top 0.5%
- Artificial Intelligence top 5%
- Safety, Risk, Reliability and Quality top 2%
- Computational Theory and Mathematics top 5%
- Signal Processing top 5%
- Co-authors
- Karen KafadarG. W. StewartMohamed Abdel‐AtyDavid A. HarvilleJohn G. SawAnthony VodacekRobert L. KremensDon J. Latham
- Topics
- Advanced Statistical Methods and Models (25 papers)Optimal Experimental Design Methods (9 papers)Statistical Methods and Inference (8 papers)
- Journals
- Journal of the American Statistical AssociationBiometrikaInternational Journal of Remote Sensing
- Partner nations
- United States
In The Last Decade
James R. Schott
44 papers receiving 1.6k citations
Hit Papers
Peers
Comparison fields: 5 of 147
- Statistics and Probability 745
- Artificial Intelligence 346
- Safety, Risk, Reliability and Quality 142
- Computational Theory and Mathematics 133
- Signal Processing 130
Countries citing papers authored by James R. Schott
This map shows the geographic impact of James R. Schott'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 James R. Schott with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites James R. Schott more than expected).
Fields of papers citing papers by James R. Schott
This network shows the impact of papers produced by James R. Schott. 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 James R. Schott. The network helps show where James R. Schott may publish in the future.
Co-authorship network of co-authors of James R. Schott
This figure shows the co-authorship network connecting the top 25 collaborators of James R. Schott. A scholar is included among the top collaborators of James R. Schott 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 James R. Schott. James R. Schott 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 | 55 | |
| 3 | 97 | |
| 4 | 5 | |
| 5 | 43 | |
| 6 | 18 | |
| 7 | 4 | |
| 8 | 5 | |
| 9 | 49 | |
| 10 | 27 | |
| 11 | 10 | |
| 12 | 110 | |
| 13 | 31 | |
| 14 | 90 | |
| 15 | 4 | |
| 16 | 6 | |
| 17 | 5 | |
| 18 | 21 | |
| 19 | 19 | |
| 20 | 20 |
About James R. Schott
James R. Schott is a scholar working on Statistics and Probability, Analytical Chemistry and Management Science and Operations Research, having authored 46 papers that have together received 1.6k indexed citations. Recurring topics across this work include Advanced Statistical Methods and Models (25 papers), Optimal Experimental Design Methods (9 papers) and Statistical Methods and Inference (8 papers). The work is most often cited by research in Statistics and Probability (745 citations), Computational Mathematics (24 citations) and Safety, Risk, Reliability and Quality (142 citations). James R. Schott has collaborated with scholars based in United States. Frequent co-authors include Karen Kafadar, G. W. Stewart, Mohamed Abdel‐Aty, David A. Harville, John G. Saw, Anthony Vodacek, Robert L. Kremens, Don J. Latham and Mortaza Jamshidian. Their work appears in journals such as Journal of the American Statistical Association, Biometrika and International Journal of Remote Sensing.
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.