Jim Q. Smith
- Artificial Intelligence top 10%
- Management Science and Operations Research top 10%
- Statistics and Probability top 5%
- Signal Processing top 10%
- Statistics, Probability and Uncertainty top 10%
- Co-authors
- Raffaella SettimiPiotr ZwiernikG. H. FreemanLi WangNick ParsonsE. C. ZeemanP. J. HarrisonJane L. Hutton
- Topics
- Bayesian Modeling and Causal Inference (22 papers)Statistical Methods and Inference (9 papers)Bayesian Methods and Mixture Models (5 papers)
- Cited by
- Statistics and ProbabilityManagement Science and Operations ResearchStatistics, Probability and Uncertainty
- Journals
- European Journal of Operational ResearchBiometrikaJournal of the Royal Statistical Society Series B (Statistical Methodology)
- Partner nations
- United KingdomAustraliaUnited States
In The Last Decade
Jim Q. Smith
28 papers receiving 241 citations
Peers
Comparison fields: 5 of 79
- Artificial Intelligence 122
- Management Science and Operations Research 64
- Statistics and Probability 55
- Signal Processing 44
- Statistics, Probability and Uncertainty 33
Countries citing papers authored by Jim Q. Smith
This map shows the geographic impact of Jim Q. Smith'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 Jim Q. Smith with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jim Q. Smith more than expected).
Fields of papers citing papers by Jim Q. Smith
This network shows the impact of papers produced by Jim Q. Smith. 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 Jim Q. Smith. The network helps show where Jim Q. Smith may publish in the future.
Co-authorship network of co-authors of Jim Q. Smith
This figure shows the co-authorship network connecting the top 25 collaborators of Jim Q. Smith. A scholar is included among the top collaborators of Jim Q. Smith 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 Jim Q. Smith. Jim Q. Smith 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 | 2 | |
| 5 | Principled Bayesian Minimum Divergence Inference | 2 |
| 6 | The correlation space of Gaussian latent tree models | 0 |
| 7 | 13 | |
| 8 | 11 | |
| 9 | 46 | |
| 10 | Evaluating Causal effects using Chain Event Graphs. | 3 |
| 11 | From Simple Prescriptive to Complex Descriptive Models: An Example from a Recent Command Decision Experiment | 2 |
| 12 | Multicausal Prior Families, Randomisation and Essential Graphs. | 4 |
| 13 | 17 | |
| 14 | Geometry, moments and Bayesian networks with hidden variables. | 7 |
| 15 | 8 | |
| 16 | 0 | |
| 17 | 3 | |
| 18 | 29 | |
| 19 | 4 | |
| 20 | 10 |
About Jim Q. Smith
Jim Q. Smith is a scholar working on Statistics and Probability, Artificial Intelligence and Management Science and Operations Research, having authored 36 papers that have together received 263 indexed citations. Recurring topics across this work include Bayesian Modeling and Causal Inference (22 papers), Statistical Methods and Inference (9 papers) and Bayesian Methods and Mixture Models (5 papers). The work is most often cited by research in Statistics and Probability (55 citations), Management Science and Operations Research (64 citations) and Statistics, Probability and Uncertainty (33 citations). Jim Q. Smith has collaborated with scholars based in United Kingdom, Australia and United States. Frequent co-authors include Raffaella Settimi, Piotr Zwiernik, G. H. Freeman, Li Wang, Nick Parsons, E. C. Zeeman, P. J. Harrison, Jane L. Hutton, Ann E. Nicholson and Eva Riccomagno. Their work appears in journals such as European Journal of Operational Research, Biometrika and Journal of the Royal Statistical Society Series B (Statistical Methodology).
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.