M. J. Bayarri
- Statistics and Probability top 0.2%
- Statistical Methods and Bayesian Inference 13
- Advanced Statistical Methods and Models 9
- Statistical Methods and Inference 9
- Statistical Methods in Clinical Trials 5
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- Advanced Statistical Process Monitoring 5
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- Advanced Multi-Objective Optimization Algorithms 4
- General Decision Sciences top 10%
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- Bayesian Methods and Mixture Models 8
- Bayesian Modeling and Causal Inference 6
- Co-authors
- James O. BergerThomas SellkeGonzalo García‐DonatoCarmen ArmeroRaymond HubbardRui PauloJ. SacksJohn A. Cafeo
- Cited by
- Statistics and ProbabilityStatistics, Probability and UncertaintyManagement Science and Operations Research
- 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
- Management Science and Operations Research 497
- Computational Theory and Mathematics 324
- General Decision Sciences 36
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
The 25 scholars most cited alongside M. J. Bayarri, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | Prior-based Bayesian information criterion | 2019 | 2 |
| 2 | 2016 | 68 | |
| 3 | 2015 | 1 | |
| 4 | Lipoatrofia semicircular de origen laboral | 2009 | 4 |
| 5 | 2009 | 14 | |
| 6 | 2009 | 26 | |
| 7 | A Framework for Validation of Computer Modelsbreakdown → | 2007 | 456 |
| 8 | 2006 | 7 | |
| 9 | 2005 | 1 | |
| 10 | 2004 | 13 | |
| 11 | 2004 | 9 | |
| 12 | 2002 | 11 | |
| 13 | 2000 | 140 | |
| 14 | Graphical models for hierarchical computations in the analysis and design of replications | 1999 | 2 |
| 15 | 1998 | 13 | |
| 16 | 1994 | 61 | |
| 17 | 1992 | 2 | |
| 18 | 1991 | 2 | |
| 19 | 1991 | 7 | |
| 20 | 1988 | 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), Statistical Methods and Inference (9 papers), Bayesian Methods and Mixture Models (8 papers), Bayesian Modeling and Causal Inference (6 papers), Advanced Statistical Process Monitoring (5 papers), Statistical Methods in Clinical Trials (5 papers) and Advanced Multi-Objective Optimization Algorithms (4 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.
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.