M. J. Bayarri
- Statistics and Probability top 0.2%
- Statistics, Probability and Uncertainty top 0.2%
- Artificial Intelligence top 2%
- Management Science and Operations Research top 1%
- Computational Theory and Mathematics top 2%
- Co-authors
- James O. BergerThomas SellkeGonzalo García‐DonatoCarmen ArmeroRaymond HubbardRui PauloJ. SacksJohn A. Cafeo
- Topics
- Statistical Methods and Bayesian Inference (13 papers)Advanced Statistical Methods and Models (9 papers)Statistical Methods and Inference (9 papers)
- Cited by
- Statistics and ProbabilityStatistics, Probability and UncertaintyManagement Science and Operations Research
- Journals
- SHILAP Revista de lepidopterologíaJournal of the American Statistical AssociationTechnometrics
- Partner nations
- SpainUnited StatesUnited Kingdom
In The Last Decade
M. J. Bayarri
52 papers receiving 2.5k citations
Hit Papers
Peers
Comparison fields: 5 of 178
- Statistics and Probability 1.0k
- Statistics, Probability and Uncertainty 736
- Artificial Intelligence 621
- Management Science and Operations Research 497
- Computational Theory and Mathematics 324
Countries citing papers authored by M. J. Bayarri
This map shows the geographic impact of M. J. Bayarri'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 M. J. Bayarri with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites M. J. Bayarri more than expected).
Fields of papers citing papers by M. J. Bayarri
This network shows the impact of papers produced by M. J. Bayarri. 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 M. J. Bayarri. The network helps show where M. J. Bayarri may publish in the future.
Co-authorship network of co-authors of M. J. Bayarri
This figure shows the co-authorship network connecting the top 25 collaborators of M. J. Bayarri. A scholar is included among the top collaborators of M. J. Bayarri 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 M. J. Bayarri. M. J. Bayarri is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | Prior-based Bayesian information criterion | 2 |
| 2 | 68 | |
| 3 | 1 | |
| 4 | Lipoatrofia semicircular de origen laboral | 4 |
| 5 | 14 | |
| 6 | 26 | |
| 7 | A Framework for Validation of Computer Modelsbreakdown → | 456 |
| 8 | 7 | |
| 9 | 1 | |
| 10 | 13 | |
| 11 | 9 | |
| 12 | 11 | |
| 13 | 140 | |
| 14 | Graphical models for hierarchical computations in the analysis and design of replications | 2 |
| 15 | 13 | |
| 16 | 61 | |
| 17 | 2 | |
| 18 | 2 | |
| 19 | 7 | |
| 20 | 2 |
About M. J. Bayarri
M. J. Bayarri is a scholar working on Statistics and Probability, Statistics, Probability and Uncertainty and Management Science and Operations Research, having authored 54 papers that have together received 2.6k indexed citations. Recurring topics across this work include Statistical Methods and Bayesian Inference (13 papers), Advanced Statistical Methods and Models (9 papers) and Statistical Methods and Inference (9 papers). The work is most often cited by research in Statistics and Probability (1.0k citations), Statistics, Probability and Uncertainty (736 citations) and Management Science and Operations Research (497 citations). M. J. Bayarri has collaborated with scholars based in Spain, United States and United Kingdom. Frequent co-authors include James O. Berger, Thomas Sellke, Gonzalo García‐Donato, Carmen Armero, Raymond Hubbard, Rui Paulo, J. Sacks, John A. Cafeo, Jian Tu and James C. Cavendish. Their work appears in journals such as SHILAP Revista de lepidopterología, Journal of the American Statistical Association and Technometrics.
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.