Aldo M. Garay
- Statistics and Probability top 2%
- Artificial Intelligence top 10%
- Statistics, Probability and Uncertainty top 10%
- Finance
- Economics and Econometrics
- Co-authors
- Víctor H. LachosEdwin M. M. OrtegaElizabeth M. HashimotoCelso Rômulo Barbosa CabralHeleno BolfarineCarlos A. Abanto‐ValleDipankar BandyopadhyayLuis M. Castro
- Topics
- Statistical Distribution Estimation and Applications (14 papers)Bayesian Methods and Mixture Models (13 papers)Statistical Methods and Bayesian Inference (12 papers)
- Journals
- Computational Statistics & Data AnalysisStatistical Methods in Medical ResearchJournal of Statistical Planning and Inference
- Partner nations
- BrazilUnited StatesTaiwan
In The Last Decade
Aldo M. Garay
16 papers receiving 300 citations
Peers
Comparison fields: 5 of 77
- Statistics and Probability 230
- Artificial Intelligence 130
- Statistics, Probability and Uncertainty 27
- Finance 26
- Economics and Econometrics 26
Countries citing papers authored by Aldo M. Garay
This map shows the geographic impact of Aldo M. Garay'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 Aldo M. Garay with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Aldo M. Garay more than expected).
Fields of papers citing papers by Aldo M. Garay
This network shows the impact of papers produced by Aldo M. Garay. 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 Aldo M. Garay. The network helps show where Aldo M. Garay may publish in the future.
Co-authorship network of co-authors of Aldo M. Garay
This figure shows the co-authorship network connecting the top 25 collaborators of Aldo M. Garay. A scholar is included among the top collaborators of Aldo M. Garay 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 Aldo M. Garay. Aldo M. Garay 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 | 6 | |
| 6 | 6 | |
| 7 | 18 | |
| 8 | 6 | |
| 9 | 11 | |
| 10 | 9 | |
| 11 | 11 | |
| 12 | 21 | |
| 13 | 34 | |
| 14 | 14 | |
| 15 | 12 | |
| 16 | 24 | |
| 17 | 14 | |
| 18 | 20 | |
| 19 | 96 |
About Aldo M. Garay
Aldo M. Garay is a scholar working on Statistics and Probability, Artificial Intelligence and Finance, having authored 19 papers that have together received 304 indexed citations. Recurring topics across this work include Statistical Distribution Estimation and Applications (14 papers), Bayesian Methods and Mixture Models (13 papers) and Statistical Methods and Bayesian Inference (12 papers). The work is most often cited by research in Statistics and Probability (230 citations), Artificial Intelligence (130 citations) and Statistics, Probability and Uncertainty (27 citations). Aldo M. Garay has collaborated with scholars based in Brazil, United States and Taiwan. Frequent co-authors include Víctor H. Lachos, Edwin M. M. Ortega, Elizabeth M. Hashimoto, Celso Rômulo Barbosa Cabral, Heleno Bolfarine, Carlos A. Abanto‐Valle, Dipankar Bandyopadhyay, Luis M. Castro, Jacek Leśkow and Tsung‐I Lin. Their work appears in journals such as Computational Statistics & Data Analysis, Statistical Methods in Medical Research and Journal of Statistical Planning and Inference.
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.