Walter Racugno
- Statistics and Probability top 1%
- Artificial Intelligence top 10%
- Statistics, Probability and Uncertainty top 2%
- Management Science and Operations Research top 10%
- Economics and Econometrics
- Co-authors
- Laura VenturaElı́as MorenoFrancesco PauliLuca GrecoAlessandra SalvanPaolo GirardiNicola SartoriStefano Cabras
- Topics
- Statistical Methods and Bayesian Inference (17 papers)Advanced Statistical Methods and Models (13 papers)Statistical Methods and Inference (9 papers)
- Cited by
- Statistics and ProbabilityStatistics, Probability and UncertaintyManagement Science and Operations Research
In The Last Decade
Walter Racugno
22 papers receiving 410 citations
Peers
Comparison fields: 5 of 62
- Statistics and Probability 364
- Artificial Intelligence 110
- Statistics, Probability and Uncertainty 90
- Management Science and Operations Research 58
- Economics and Econometrics 25
Countries citing papers authored by Walter Racugno
This map shows the geographic impact of Walter Racugno'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 Walter Racugno with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Walter Racugno more than expected).
Fields of papers citing papers by Walter Racugno
This network shows the impact of papers produced by Walter Racugno. 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 Walter Racugno. The network helps show where Walter Racugno may publish in the future.
Co-authorship network of co-authors of Walter Racugno
This figure shows the co-authorship network connecting the top 25 collaborators of Walter Racugno. A scholar is included among the top collaborators of Walter Racugno 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 Walter Racugno. Walter Racugno 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 | 14 | |
| 3 | Default Bayesian inference for the consensus mean in inter-laboratory studies | 0 |
| 4 | 3 | |
| 5 | 6 | |
| 6 | 29 | |
| 7 | 21 | |
| 8 | A note on the relationships between Bayesian and non-Bayesian predictive inference | 1 |
| 9 | 8 | |
| 10 | 30 | |
| 11 | On the use of pseudo-likelihoods in Bayesian variable selection | 1 |
| 12 | 9 | |
| 13 | 26 | |
| 14 | 27 | |
| 15 | 93 | |
| 16 | 8 | |
| 17 | 4 | |
| 18 | 8 | |
| 19 | 5 | |
| 20 | 82 |
About Walter Racugno
Walter Racugno is a scholar working on Statistics and Probability, Statistics, Probability and Uncertainty and Modeling and Simulation, having authored 24 papers that have together received 436 indexed citations. Recurring topics across this work include Statistical Methods and Bayesian Inference (17 papers), Advanced Statistical Methods and Models (13 papers) and Statistical Methods and Inference (9 papers). The work is most often cited by research in Statistics and Probability (364 citations), Statistics, Probability and Uncertainty (90 citations) and Management Science and Operations Research (58 citations). Walter Racugno has collaborated with scholars based in Italy, Spain and India. Frequent co-authors include Laura Ventura, Elı́as Moreno, Francesco Pauli, Luca Greco, Alessandra Salvan, Paolo Girardi, Nicola Sartori, Stefano Cabras and Monica Musio. Their work appears in journals such as Journal of the American Statistical Association, American Mathematical Monthly and Computational Statistics & Data Analysis.
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.