Emma J. McCoy
- Economics and Econometrics top 10%
- Finance top 5%
- Statistics and Probability top 5%
- Signal Processing top 5%
- Computer Vision and Pattern Recognition top 10%
- Co-authors
- Andrew T. WaldenDonald B. PercivalDavid A. StephensDaniel J. GrahamAjay JasraSumeetpal S. SinghChristoforos AnagnostopoulosAudrey de Nazelle
- Topics
- Urban Transport and Accessibility (8 papers)Statistical Methods and Bayesian Inference (6 papers)Statistical Methods and Inference (5 papers)
- Journals
- Journal of the American Statistical AssociationPLoS ONEIEEE Transactions on Signal Processing
- Partner nations
- United KingdomUnited StatesSpain
In The Last Decade
Emma J. McCoy
30 papers receiving 593 citations
Peers
Comparison fields: 5 of 116
- Economics and Econometrics 148
- Finance 111
- Statistics and Probability 111
- Signal Processing 109
- Computer Vision and Pattern Recognition 108
Countries citing papers authored by Emma J. McCoy
This map shows the geographic impact of Emma J. McCoy'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 Emma J. McCoy with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Emma J. McCoy more than expected).
Fields of papers citing papers by Emma J. McCoy
This network shows the impact of papers produced by Emma J. McCoy. 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 Emma J. McCoy. The network helps show where Emma J. McCoy may publish in the future.
Co-authorship network of co-authors of Emma J. McCoy
This figure shows the co-authorship network connecting the top 25 collaborators of Emma J. McCoy. A scholar is included among the top collaborators of Emma J. McCoy 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 Emma J. McCoy. Emma J. McCoy 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 | 2 | |
| 4 | 2 | |
| 5 | 4 | |
| 6 | 2 | |
| 7 | 24 | |
| 8 | 1 | |
| 9 | 21 | |
| 10 | 29 | |
| 11 | 15 | |
| 12 | 20 | |
| 13 | 4 | |
| 14 | 14 | |
| 15 | 50 | |
| 16 | 15 | |
| 17 | 62 | |
| 18 | 89 | |
| 19 | 47 | |
| 20 | 47 |
About Emma J. McCoy
Emma J. McCoy is a scholar working on Statistics and Probability, Transportation and Finance, having authored 33 papers that have together received 633 indexed citations. Recurring topics across this work include Urban Transport and Accessibility (8 papers), Statistical Methods and Bayesian Inference (6 papers) and Statistical Methods and Inference (5 papers). The work is most often cited by research in Statistics and Probability (111 citations), Finance (111 citations) and Signal Processing (109 citations). Emma J. McCoy has collaborated with scholars based in United Kingdom, United States and Spain. Frequent co-authors include Andrew T. Walden, Donald B. Percival, David A. Stephens, Daniel J. Graham, Ajay Jasra, Sumeetpal S. Singh, Christoforos Anagnostopoulos, Audrey de Nazelle, Haojie Li and Pierre Del Moral. Their work appears in journals such as Journal of the American Statistical Association, PLoS ONE and IEEE Transactions on Signal Processing.
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.