Joan del Castillo
- Statistics and Probability top 2%
- Artificial Intelligence
- Finance top 10%
- Statistics, Probability and Uncertainty top 5%
- Economics and Econometrics
- Co-authors
- Marta Pérez‐CasanyPedro PuigJaume AbellaFrancisco J. CazorlaJoaquim BrunaYoungjo LeeRichard LockhartJohan Lim
- Topics
- Statistical Distribution Estimation and Applications (12 papers)Financial Risk and Volatility Modeling (10 papers)Bayesian Methods and Mixture Models (6 papers)
- Journals
- Journal of the American Statistical AssociationComputational Statistics & Data AnalysisMathematische Annalen
- Partner nations
- SpainUnited StatesCanada
In The Last Decade
Joan del Castillo
28 papers receiving 380 citations
Peers
Comparison fields: 5 of 78
- Statistics and Probability 182
- Artificial Intelligence 74
- Finance 62
- Statistics, Probability and Uncertainty 57
- Economics and Econometrics 55
Countries citing papers authored by Joan del Castillo
This map shows the geographic impact of Joan del Castillo'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 Joan del Castillo with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Joan del Castillo more than expected).
Fields of papers citing papers by Joan del Castillo
This network shows the impact of papers produced by Joan del Castillo. 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 Joan del Castillo. The network helps show where Joan del Castillo may publish in the future.
Co-authorship network of co-authors of Joan del Castillo
This figure shows the co-authorship network connecting the top 25 collaborators of Joan del Castillo. A scholar is included among the top collaborators of Joan del Castillo 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 Joan del Castillo. Joan del Castillo 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 | 1 | |
| 3 | 1 | |
| 4 | 2 | |
| 5 | THE FULL TAILS GAMMA DISTRIBUTION APPLIED to MODEL EXTREME VALUES | 5 |
| 6 | 0 | |
| 7 | 49 | |
| 8 | 3 | |
| 9 | Modelling extreme values by the residual coefficient of variation | 4 |
| 10 | 2 | |
| 11 | 15 | |
| 12 | 21 | |
| 13 | 8 | |
| 14 | Origen, espacio y niveles de participación ciudadana (Origin, space and levels of participation) | 0 |
| 15 | 3 | |
| 16 | 9 | |
| 17 | 2 | |
| 18 | 9 | |
| 19 | 31 | |
| 20 | 54 |
About Joan del Castillo
Joan del Castillo is a scholar working on Statistics and Probability, Finance and Statistics, Probability and Uncertainty, having authored 32 papers that have together received 399 indexed citations. Recurring topics across this work include Statistical Distribution Estimation and Applications (12 papers), Financial Risk and Volatility Modeling (10 papers) and Bayesian Methods and Mixture Models (6 papers). The work is most often cited by research in Statistics and Probability (182 citations), Statistics, Probability and Uncertainty (57 citations) and Hardware and Architecture (44 citations). Joan del Castillo has collaborated with scholars based in Spain, United States and Canada. Frequent co-authors include Marta Pérez‐Casany, Pedro Puig, Jaume Abella, Francisco J. Cazorla, Joaquim Bruna, Youngjo Lee, Richard Lockhart, Johan Lim, Woojoo Lee and Jacob Burbea. Their work appears in journals such as Journal of the American Statistical Association, Computational Statistics & Data Analysis and Mathematische Annalen.
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.