Lea Petrella
- Finance top 5%
- Economics and Econometrics top 5%
- Pulmonary and Respiratory Medicine top 10%
- Statistics and Probability top 2%
- Global and Planetary Change top 10%
- Co-authors
- Mauro BernardiAntonello MaruottiFilippo BellocGianfausto SalvadoriFabrizio DuranteGiuseppe CardilloFrancesco CarleoCarlo De Michele
- Topics
- Statistical Methods and Inference (20 papers)Financial Risk and Volatility Modeling (19 papers)Bayesian Methods and Mixture Models (12 papers)
- Partner nations
- ItalyUnited KingdomSpain
In The Last Decade
Lea Petrella
57 papers receiving 1.1k citations
Peers
Comparison fields: 5 of 118
- Finance 239
- Economics and Econometrics 238
- Pulmonary and Respiratory Medicine 223
- Statistics and Probability 176
- Global and Planetary Change 175
Countries citing papers authored by Lea Petrella
This map shows the geographic impact of Lea Petrella'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 Lea Petrella with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Lea Petrella more than expected).
Fields of papers citing papers by Lea Petrella
This network shows the impact of papers produced by Lea Petrella. 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 Lea Petrella. The network helps show where Lea Petrella may publish in the future.
Co-authorship network of co-authors of Lea Petrella
This figure shows the co-authorship network connecting the top 25 collaborators of Lea Petrella. A scholar is included among the top collaborators of Lea Petrella 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 Lea Petrella. Lea Petrella 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 | 5 | |
| 3 | 4 | |
| 4 | 8 | |
| 5 | 9 | |
| 6 | 3 | |
| 7 | 4 | |
| 8 | 1 | |
| 9 | 3 | |
| 10 | 37 | |
| 11 | 13 | |
| 12 | 1 | |
| 13 | 187 | |
| 14 | 9 | |
| 15 | 46 | |
| 16 | 5 | |
| 17 | 64 | |
| 18 | 63 | |
| 19 | Mixtures of conjugate prior distributions and large deviations for level crossing probabilities | 6 |
| 20 | 5 |
About Lea Petrella
Lea Petrella is a scholar working on Statistics and Probability, Finance and General Economics, Econometrics and Finance, having authored 64 papers that have together received 1.2k indexed citations. Recurring topics across this work include Statistical Methods and Inference (20 papers), Financial Risk and Volatility Modeling (19 papers) and Bayesian Methods and Mixture Models (12 papers). The work is most often cited by research in Finance (239 citations), Statistics and Probability (176 citations) and Management Science and Operations Research (136 citations). Lea Petrella has collaborated with scholars based in Italy, United Kingdom and Spain. Frequent co-authors include Mauro Bernardi, Antonello Maruotti, Filippo Belloc, Gianfausto Salvadori, Fabrizio Durante, Giuseppe Cardillo, Francesco Carleo, Carlo De Michele, Maria Paola Martelli and Lorenzo Salvadori. Their work appears in journals such as Journal of the American Statistical Association, Water Resources Research and Biometrika.
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.