Monica Musio
- Statistics and Probability top 5%
- Artificial Intelligence
- Economics and Econometrics
- Global and Planetary Change
- Nature and Landscape Conservation
- Co-authors
- A. P. DawidNicole H. AugustinKlaus von WilpertLaura VenturaEdgar KublinMartin SchumacherSimon N. WoodErik Sauleau
- Topics
- Advanced Statistical Methods and Models (9 papers)Statistical Methods and Bayesian Inference (8 papers)Statistical Methods and Inference (6 papers)
- Cited by
- Statistics and ProbabilityNature and Landscape ConservationStatistics, Probability and Uncertainty
- Journals
- Journal of the American Statistical AssociationEcological ModellingJournal of the Royal Statistical Society Series C (Applied Statistics)
- Partner nations
- ItalyUnited KingdomGermany
In The Last Decade
Monica Musio
31 papers receiving 368 citations
Peers
Comparison fields: 5 of 110
- Statistics and Probability 126
- Artificial Intelligence 68
- Economics and Econometrics 66
- Global and Planetary Change 54
- Nature and Landscape Conservation 49
Countries citing papers authored by Monica Musio
This map shows the geographic impact of Monica Musio'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 Monica Musio with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Monica Musio more than expected).
Fields of papers citing papers by Monica Musio
This network shows the impact of papers produced by Monica Musio. 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 Monica Musio. The network helps show where Monica Musio may publish in the future.
Co-authorship network of co-authors of Monica Musio
This figure shows the co-authorship network connecting the top 25 collaborators of Monica Musio. A scholar is included among the top collaborators of Monica Musio 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 Monica Musio. Monica Musio is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 2 | |
| 2 | 0 | |
| 3 | 2 | |
| 4 | 6 | |
| 5 | 2 | |
| 6 | 4 | |
| 7 | 0 | |
| 8 | 14 | |
| 9 | 16 | |
| 10 | 5 | |
| 11 | 0 | |
| 12 | Comparison of approaches to inference in stationary AR(1) models | 1 |
| 13 | 6 | |
| 14 | 2 | |
| 15 | 7 | |
| 16 | 21 | |
| 17 | 74 | |
| 18 | 11 | |
| 19 | 16 | |
| 20 | 2 |
About Monica Musio
Monica Musio is a scholar working on Statistics and Probability, Statistics, Probability and Uncertainty and Nature and Landscape Conservation, having authored 35 papers that have together received 379 indexed citations. Recurring topics across this work include Advanced Statistical Methods and Models (9 papers), Statistical Methods and Bayesian Inference (8 papers) and Statistical Methods and Inference (6 papers). The work is most often cited by research in Statistics and Probability (126 citations), Nature and Landscape Conservation (49 citations) and Statistics, Probability and Uncertainty (28 citations). Monica Musio has collaborated with scholars based in Italy, United Kingdom and Germany. Frequent co-authors include A. P. Dawid, Nicole H. Augustin, Klaus von Wilpert, Laura Ventura, Edgar Kublin, Martin Schumacher, Simon N. Wood, Erik Sauleau, A. Buémi and Stephen E. Fienberg. Their work appears in journals such as Journal of the American Statistical Association, Ecological Modelling and Journal of the Royal Statistical Society Series C (Applied Statistics).
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.