Fernando A. Quintana
- Statistics and Probability top 0.2%
- Artificial Intelligence top 1%
- Statistics, Probability and Uncertainty top 1%
- Finance top 5%
- Management Science and Operations Research top 5%
- Co-authors
- Peter MüllerAlejandro JaraHéctor W. GómezGary L. RosnerReinaldo B. Arellano‐ValleRolando de la CruzMichael A. NewtonTimothy Hanson
- Topics
- Bayesian Methods and Mixture Models (55 papers)Statistical Methods and Bayesian Inference (33 papers)Statistical Methods and Inference (30 papers)
- Journals
- SHILAP Revista de lepidopterologíaJournal of the American Statistical AssociationBiometrics
- Partner nations
- ChileUnited StatesArgentina
In The Last Decade
Fernando A. Quintana
78 papers receiving 1.8k citations
Peers
Comparison fields: 5 of 134
- Statistics and Probability 1.2k
- Artificial Intelligence 1.2k
- Statistics, Probability and Uncertainty 201
- Finance 177
- Management Science and Operations Research 142
Countries citing papers authored by Fernando A. Quintana
This map shows the geographic impact of Fernando A. Quintana'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 Fernando A. Quintana with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Fernando A. Quintana more than expected).
Fields of papers citing papers by Fernando A. Quintana
This network shows the impact of papers produced by Fernando A. Quintana. 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 Fernando A. Quintana. The network helps show where Fernando A. Quintana may publish in the future.
Co-authorship network of co-authors of Fernando A. Quintana
This figure shows the co-authorship network connecting the top 25 collaborators of Fernando A. Quintana. A scholar is included among the top collaborators of Fernando A. Quintana 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 Fernando A. Quintana. Fernando A. Quintana 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 | 3 | |
| 3 | 11 | |
| 4 | 1 | |
| 5 | 7 | |
| 6 | 25 | |
| 7 | 0 | |
| 8 | 6 | |
| 9 | DPpackage: Bayesian Semi- and Nonparametric Modeling in R | 1 |
| 10 | 4 | |
| 11 | 15 | |
| 12 | 42 | |
| 13 | 40 | |
| 14 | 6 | |
| 15 | 10 | |
| 16 | 18 | |
| 17 | 64 | |
| 18 | 8 | |
| 19 | 113 | |
| 20 | 23 |
About Fernando A. Quintana
Fernando A. Quintana is a scholar working on Statistics and Probability, Artificial Intelligence and Tourism, Leisure and Hospitality Management, having authored 80 papers that have together received 1.9k indexed citations. Recurring topics across this work include Bayesian Methods and Mixture Models (55 papers), Statistical Methods and Bayesian Inference (33 papers) and Statistical Methods and Inference (30 papers). The work is most often cited by research in Statistics and Probability (1.2k citations), Artificial Intelligence (1.2k citations) and Statistics, Probability and Uncertainty (201 citations). Fernando A. Quintana has collaborated with scholars based in Chile, United States and Argentina. Frequent co-authors include Peter Müller, Alejandro Jara, Héctor W. Gómez, Gary L. Rosner, Reinaldo B. Arellano‐Valle, Rolando de la Cruz, Michael A. Newton, Timothy Hanson, Tim Hanson and Ernesto San Martı́n. Their work appears in journals such as SHILAP Revista de lepidopterología, Journal of the American Statistical Association and Biometrics.
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.