Jacobo de Uña‐Álvarez
- Statistics and Probability top 0.5%
- Artificial Intelligence top 5%
- Molecular Biology
- Economics and Econometrics top 10%
- Management Science and Operations Research top 5%
- Co-authors
- Luís Meira‐MachadoCarmén Cadarso-SuárezPer Kragh AndersenAntonio Carvajal‐RodríguezCarla MoreiraEmilio Rolán‐AlvarezHan‐Ying LiangNoël Veraverbeke
- Topics
- Statistical Methods and Inference (67 papers)Statistical Methods and Bayesian Inference (33 papers)Statistical Distribution Estimation and Applications (32 papers)
In The Last Decade
Jacobo de Uña‐Álvarez
91 papers receiving 1.6k citations
Peers
Comparison fields: 5 of 160
- Statistics and Probability 876
- Artificial Intelligence 287
- Molecular Biology 122
- Economics and Econometrics 121
- Management Science and Operations Research 99
Countries citing papers authored by Jacobo de Uña‐Álvarez
This map shows the geographic impact of Jacobo de Uña‐Álvarez'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 Jacobo de Uña‐Álvarez with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jacobo de Uña‐Álvarez more than expected).
Fields of papers citing papers by Jacobo de Uña‐Álvarez
This network shows the impact of papers produced by Jacobo de Uña‐Álvarez. 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 Jacobo de Uña‐Álvarez. The network helps show where Jacobo de Uña‐Álvarez may publish in the future.
Co-authorship network of co-authors of Jacobo de Uña‐Álvarez
This figure shows the co-authorship network connecting the top 25 collaborators of Jacobo de Uña‐Álvarez. A scholar is included among the top collaborators of Jacobo de Uña‐Álvarez 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 Jacobo de Uña‐Álvarez. Jacobo de Uña‐Álvarez 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 | 0 | |
| 3 | 2 | |
| 4 | 0 | |
| 5 | 5 | |
| 6 | 2 | |
| 7 | 1 | |
| 8 | 7 | |
| 9 | 9 | |
| 10 | 7 | |
| 11 | 65 | |
| 12 | 37 | |
| 13 | 8 | |
| 14 | 28 | |
| 15 | 138 | |
| 16 | Inference in multi-state survival data | 1 |
| 17 | Comparison of two methods for analysing the biological factors contributing to assortative mating or sexual isolation | 2 |
| 18 | 3 | |
| 19 | 7 | |
| 20 | 5 |
About Jacobo de Uña‐Álvarez
Jacobo de Uña‐Álvarez is a scholar working on Statistics and Probability, Statistics, Probability and Uncertainty and Management Science and Operations Research, having authored 94 papers that have together received 1.6k indexed citations. Recurring topics across this work include Statistical Methods and Inference (67 papers), Statistical Methods and Bayesian Inference (33 papers) and Statistical Distribution Estimation and Applications (32 papers). The work is most often cited by research in Statistics and Probability (876 citations), Statistics, Probability and Uncertainty (81 citations) and Artificial Intelligence (287 citations). Jacobo de Uña‐Álvarez has collaborated with scholars based in Spain, Portugal and China. Frequent co-authors include Luís Meira‐Machado, Carmén Cadarso-Suárez, Per Kragh Andersen, Antonio Carvajal‐Rodríguez, Carla Moreira, Emilio Rolán‐Alvarez, Han‐Ying Liang, Noël Veraverbeke, Alberto Rodríguez‐Casal and J. S. Marron. Their work appears in journals such as PLoS ONE, Biometrics and Journal of Bacteriology.
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.