Luis M. Castro
- Statistics and Probability top 1%
- Artificial Intelligence top 10%
- Management Science and Operations Research top 10%
- Statistics, Probability and Uncertainty top 5%
- Finance top 10%
- Co-authors
- Víctor H. LachosReinaldo B. Arellano‐ValleDipak K. DeyWan‐Lun WangHéctor W. GómezTsung‐I LinDipankar BandyopadhyayErnesto San Martı́n
- Topics
- Statistical Methods and Bayesian Inference (27 papers)Bayesian Methods and Mixture Models (22 papers)Statistical Distribution Estimation and Applications (22 papers)
- Journals
- Proceedings of the National Academy of SciencesJournal of the American Statistical AssociationBiometrics
- Partner nations
- ChileBrazilUnited States
In The Last Decade
Luis M. Castro
41 papers receiving 407 citations
Peers
Comparison fields: 5 of 77
- Statistics and Probability 334
- Artificial Intelligence 188
- Management Science and Operations Research 45
- Statistics, Probability and Uncertainty 43
- Finance 38
Countries citing papers authored by Luis M. Castro
This map shows the geographic impact of Luis M. Castro'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 Luis M. Castro with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Luis M. Castro more than expected).
Fields of papers citing papers by Luis M. Castro
This network shows the impact of papers produced by Luis M. Castro. 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 Luis M. Castro. The network helps show where Luis M. Castro may publish in the future.
Co-authorship network of co-authors of Luis M. Castro
This figure shows the co-authorship network connecting the top 25 collaborators of Luis M. Castro. A scholar is included among the top collaborators of Luis M. Castro 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 Luis M. Castro. Luis M. Castro 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 | 1 | |
| 3 | 0 | |
| 4 | 0 | |
| 5 | 7 | |
| 6 | 4 | |
| 7 | 5 | |
| 8 | 9 | |
| 9 | 2 | |
| 10 | 5 | |
| 11 | 18 | |
| 12 | 8 | |
| 13 | 5 | |
| 14 | 7 | |
| 15 | 3 | |
| 16 | 8 | |
| 17 | 6 | |
| 18 | 26 | |
| 19 | 29 | |
| 20 | Calidad de la educación matemática en secundaria. Actores y procesos en la institución educativa | 4 |
About Luis M. Castro
Luis M. Castro is a scholar working on Statistics and Probability, Artificial Intelligence and Statistics, Probability and Uncertainty, having authored 44 papers that have together received 415 indexed citations. Recurring topics across this work include Statistical Methods and Bayesian Inference (27 papers), Bayesian Methods and Mixture Models (22 papers) and Statistical Distribution Estimation and Applications (22 papers). The work is most often cited by research in Statistics and Probability (334 citations), Statistics, Probability and Uncertainty (43 citations) and Artificial Intelligence (188 citations). Luis M. Castro has collaborated with scholars based in Chile, Brazil and United States. Frequent co-authors include Víctor H. Lachos, Reinaldo B. Arellano‐Valle, Dipak K. Dey, Wan‐Lun Wang, Héctor W. Gómez, Tsung‐I Lin, Dipankar Bandyopadhyay, Ernesto San Martı́n, Graciela González–Farías and Marc G. Genton. Their work appears in journals such as Proceedings of the National Academy of Sciences, 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.