J.A. Pardo
Impact in
- Statistics and Probability top 2%
- Advanced Statistical Methods and Models
- Statistical Methods and Inference
- Statistical Methods and Bayesian Inference
- Statistical Distribution Estimation and Applications
- Fuzzy Systems and Optimization
- Artificial Intelligence top 10%
- Bayesian Methods and Mixture Models
Papers in
-
- Advanced Statistical Methods and Models 29
- Statistical Methods and Inference 13
- Statistical Distribution Estimation and Applications 9
- Statistical Methods and Bayesian Inference 8
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- Bayesian Modeling and Causal Inference 5
- Bayesian Methods and Mixture Models 5
- Co-authors
- Leandro Pardo (21 shared papers)M. Menéndez (21 shared papers)María del Carmen Pardo (13 shared papers)K. Zografos (5 shared papers)Teresa Pérez (6 shared papers)María Dolores Esteban (1 shared paper)Inder J. Taneja (4 shared papers)Rosa G. González‐Ramírez (1 shared paper)
In The Last Decade
J.A. Pardo
42 papers receiving 440 citations
Peers
Comparison fields: 5 of 107
- Statistics and Probability 140
- Artificial Intelligence 148
- Management Science and Operations Research 45
- Signal Processing 35
- Statistics, Probability and Uncertainty 21
Countries citing papers authored by J.A. Pardo
This map shows the geographic impact of J.A. Pardo'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 J.A. Pardo with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites J.A. Pardo more than expected).
Fields of papers citing papers by J.A. Pardo
This network shows the impact of papers produced by J.A. Pardo. 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 J.A. Pardo. The network helps show where J.A. Pardo may publish in the future.
Co-authors
The 10 scholars most cited alongside J.A. Pardo, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 43 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 1997 | 272 | |
| 2 | 1997 | 17 | |
| 3 | 2002 | 16 | |
| 4 | 1988 | 11 | |
| 5 | 2000 | 11 | |
| 6 | 2005 | 10 | |
| 7 | 2007 | 10 | |
| 8 | 1997 | 8 | |
| 9 | 2005 | 7 | |
| 10 | 1986 | 7 | |
| 11 | 2003 | 6 | |
| 12 | 2001 | 6 | |
| 13 | 1989 | 6 | |
| 14 | 2003 | 6 | |
| 15 | 1995 | 5 | |
| 16 | 2001 | 4 | |
| 17 | 1999 | 4 | |
| 18 | 2005 | 4 | |
| 19 | 1993 | 4 | |
| 20 | 2007 | 4 |
About J.A. Pardo
J.A. Pardo is a scholar working on Statistics and Probability, Artificial Intelligence, Management Science and Operations Research, Statistical and Nonlinear Physics and Computational Theory and Mathematics, having authored 43 papers that have together received 453 indexed citations. Recurring topics across this work include Advanced Statistical Methods and Models (29 papers), Statistical Methods and Inference (13 papers), Multi-Criteria Decision Making (10 papers), Statistical Distribution Estimation and Applications (9 papers), Statistical Methods and Bayesian Inference (8 papers), Bayesian Modeling and Causal Inference (5 papers), Statistical Mechanics and Entropy (5 papers) and Bayesian Methods and Mixture Models (5 papers). The work is most often cited by research in Statistics and Probability (140 citations), Artificial Intelligence (148 citations), Management Science and Operations Research (45 citations), Signal Processing (35 citations) and Statistics, Probability and Uncertainty (21 citations). J.A. Pardo has collaborated with scholars based in Spain, Greece and Brazil. Frequent co-authors include Leandro Pardo, M. Menéndez, María del Carmen Pardo, K. Zografos, Teresa Pérez, María Dolores Esteban, Inder J. Taneja, Rosa G. González‐Ramírez, José‐Fernando Camacho‐Vallejo and Domingo Morales. Their work appears in journals such as Computational Statistics & Data Analysis, Kybernetes, Fuzzy Sets and Systems, Applied Mathematics Letters and Information Sciences.
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.