Fulvia Pennoni
- Statistics and Probability top 2%
- Artificial Intelligence top 10%
- Epidemiology
- General Health Professions top 10%
- Economics and Econometrics top 10%
- Co-authors
- Francesco BartolucciAlessio FarcomeniMichaela SaisanaDonald A. BrandAlbert B. LowenfelsSilvia BacciGiorgio VittadiniBrian Francis
- Topics
- Statistical Methods and Bayesian Inference (16 papers)Bayesian Methods and Mixture Models (16 papers)Statistical Methods and Inference (13 papers)
- Journals
- SHILAP Revista de lepidopterologíaPLoS ONEBiometrics
- Partner nations
- ItalyNew ZealandPoland
In The Last Decade
Fulvia Pennoni
37 papers receiving 759 citations
Peers
Comparison fields: 5 of 127
- Statistics and Probability 222
- Artificial Intelligence 195
- Epidemiology 168
- General Health Professions 113
- Economics and Econometrics 106
Countries citing papers authored by Fulvia Pennoni
This map shows the geographic impact of Fulvia Pennoni'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 Fulvia Pennoni with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Fulvia Pennoni more than expected).
Fields of papers citing papers by Fulvia Pennoni
This network shows the impact of papers produced by Fulvia Pennoni. 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 Fulvia Pennoni. The network helps show where Fulvia Pennoni may publish in the future.
Co-authorship network of co-authors of Fulvia Pennoni
This figure shows the co-authorship network connecting the top 25 collaborators of Fulvia Pennoni. A scholar is included among the top collaborators of Fulvia Pennoni 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 Fulvia Pennoni. Fulvia Pennoni 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 | 0 | |
| 3 | 0 | |
| 4 | 0 | |
| 5 | 7 | |
| 6 | 2 | |
| 7 | 14 | |
| 8 | 7 | |
| 9 | 5 | |
| 10 | 5 | |
| 11 | 30 | |
| 12 | 1 | |
| 13 | Modelling a multivariate hidden Markov process on survey data | 1 |
| 14 | 16 | |
| 15 | 49 | |
| 16 | 28 | |
| 17 | Latent Markov models: a review of a general framework for the analysis of longitudinal data with covariates | 1 |
| 18 | 207 | |
| 19 | 22 | |
| 20 | The 2005 European e-Business Readiness Index | 10 |
About Fulvia Pennoni
Fulvia Pennoni is a scholar working on Statistics and Probability, Tourism, Leisure and Hospitality Management and Artificial Intelligence, having authored 43 papers that have together received 803 indexed citations. Recurring topics across this work include Statistical Methods and Bayesian Inference (16 papers), Bayesian Methods and Mixture Models (16 papers) and Statistical Methods and Inference (13 papers). The work is most often cited by research in Statistics and Probability (222 citations), Tourism, Leisure and Hospitality Management (16 citations) and Health (57 citations). Fulvia Pennoni has collaborated with scholars based in Italy, New Zealand and Poland. Frequent co-authors include Francesco Bartolucci, Alessio Farcomeni, Michaela Saisana, Donald A. Brand, Albert B. Lowenfels, Silvia Bacci, Giorgio Vittadini, Brian Francis, Marco Gemma and Francesca Bassi. Their work appears in journals such as SHILAP Revista de lepidopterología, PLoS ONE and Biometrics.
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.