Marco Alfò

1.8k total citations
76 papers, 1.1k citations indexed

About

Marco Alfò is a scholar working on Statistics and Probability, Artificial Intelligence and Economics and Econometrics. According to data from OpenAlex, Marco Alfò has authored 76 papers receiving a total of 1.1k indexed citations (citations by other indexed papers that have themselves been cited), including 28 papers in Statistics and Probability, 24 papers in Artificial Intelligence and 9 papers in Economics and Econometrics. Recurrent topics in Marco Alfò's work include Bayesian Methods and Mixture Models (24 papers), Statistical Methods and Bayesian Inference (22 papers) and Statistical Methods and Inference (18 papers). Marco Alfò is often cited by papers focused on Bayesian Methods and Mixture Models (24 papers), Statistical Methods and Bayesian Inference (22 papers) and Statistical Methods and Inference (18 papers). Marco Alfò collaborates with scholars based in Italy, United Kingdom and Netherlands. Marco Alfò's co-authors include Fabio Attorre, Fabio Francesconi, Giovanni Trovato, Franco Bruno, Michele De Sanctis, Murray Aitkin, Antonello Maruotti, Robert Waldmann, Donatella Vicari and Francesca Martella and has published in prestigious journals such as SHILAP Revista de lepidopterología, The Journal of Clinical Endocrinology & Metabolism and Biometrics.

In The Last Decade

Marco Alfò

73 papers receiving 1.1k citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Marco Alfò Italy 19 219 184 144 130 126 76 1.1k
Mark S. Kaiser United States 16 141 0.6× 97 0.5× 154 1.1× 109 0.8× 60 0.5× 48 923
Samuel Müller Australia 22 355 1.6× 348 1.9× 66 0.5× 128 1.0× 49 0.4× 103 2.1k
Duane Steffey United States 14 317 1.4× 125 0.7× 107 0.7× 43 0.3× 56 0.4× 28 1.1k
J. Sedransk United States 18 417 1.9× 139 0.8× 133 0.9× 88 0.7× 68 0.5× 68 961
John W. Emerson United States 21 76 0.3× 112 0.6× 163 1.1× 52 0.4× 129 1.0× 42 1.8k
Walter R. Mebane United States 18 352 1.6× 245 1.3× 274 1.9× 43 0.3× 77 0.6× 37 1.4k
Udaya B. Kogalur United States 8 177 0.8× 175 1.0× 38 0.3× 29 0.2× 36 0.3× 8 1.0k
Cristiano Varin Italy 21 761 3.5× 357 1.9× 441 3.1× 31 0.2× 227 1.8× 43 2.0k
Hirofumi Michimae Japan 18 157 0.7× 30 0.2× 21 0.1× 58 0.4× 168 1.3× 65 1.2k
Kimberly F. Sellers United States 14 360 1.6× 170 0.9× 72 0.5× 27 0.2× 25 0.2× 42 986

Countries citing papers authored by Marco Alfò

Since Specialization
Citations

This map shows the geographic impact of Marco Alfò'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 Marco Alfò with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Marco Alfò more than expected).

Fields of papers citing papers by Marco Alfò

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Marco Alfò. 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 Marco Alfò. The network helps show where Marco Alfò may publish in the future.

Co-authorship network of co-authors of Marco Alfò

This figure shows the co-authorship network connecting the top 25 collaborators of Marco Alfò. A scholar is included among the top collaborators of Marco Alfò 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 Marco Alfò. Marco Alfò is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
2.
Alfò, Marco, Nicola Salvati, & Maria Giovanna Ranalli. (2023). Correction to: Finite mixtures of quantile and M-quantile regression models. Statistics and Computing. 34(1).
3.
Alfò, Marco, Margaret F. Marino, & Francesca Martella. (2023). Biclustering multivariate discrete longitudinal data. Statistics and Computing. 34(1). 1 indexed citations
4.
5.
Alfò, Marco, et al.. (2022). On the effects of taxation on growth: an empirical assessment. Macroeconomic Dynamics. 27(5). 1289–1318. 7 indexed citations
6.
Grani, Giorgio, Livia Lamartina, Marco Alfò, et al.. (2020). Selective Use of Radioactive Iodine Therapy for Papillary Thyroid Cancers With Low or Lower-Intermediate Recurrence Risk. The Journal of Clinical Endocrinology & Metabolism. 106(4). 1717–1727. 13 indexed citations
7.
Sanctis, Vitaliana De, Marco Alfò, Giovanna Gallo, et al.. (2020). Markers of Cardiotoxicity in Early Breast Cancer Patients Treated With a Hypofractionated Schedule: A Prospective Study. Clinical Breast Cancer. 21(3). e141–e149. 7 indexed citations
8.
Sanctis, Vitaliana De, Alice Di Rocco, Maria Christina Cox, et al.. (2020). Residual Site Radiotherapy After Immunochemotherapy in Primary Mediastinal B-Cell Lymphoma: A Monoinstitutional Retrospective Study. In Vivo. 34(3). 1407–1413. 1 indexed citations
9.
Pelosi, Michele, Eric Testet, Soazig Le Lay, et al.. (2017). Normal human adipose tissue functions and differentiation in patients with biallelic LPIN1 inactivating mutations. Journal of Lipid Research. 58(12). 2348–2364. 14 indexed citations
10.
Mazzucconi, Maria Gabriella, Vitaliana De Sanctis, Marco Alfò, et al.. (2014). Maternal Thrombophilia and Adverse Pregnancy Outcome: A Case-Control Study. Acta Haematologica. 133(2). 242–248. 5 indexed citations
11.
Vicari, Donatella & Marco Alfò. (2013). Model based clustering of customer choice data. Computational Statistics & Data Analysis. 71. 3–13. 9 indexed citations
12.
Sanctis, Vitaliana De, F. Filippone, Marco Alfò, et al.. (2012). Impact of Different Treatment Approaches on Pregnancy Outcomes in 99 Women Treated for Hodgkin Lymphoma. International Journal of Radiation Oncology*Biology*Physics. 84(3). 755–761. 12 indexed citations
13.
Alfò, Marco, Alessio Farcomeni, & Luca Tardella. (2011). A Three Component Latent Class Model for Robust Semiparametric Gene Discovery. Statistical Applications in Genetics and Molecular Biology. 10(1). Article 7–Article 7. 1 indexed citations
14.
Alfò, Marco & Antonello Maruotti. (2009). A selection model for longitudinal binary responses subject to non‐ignorable attrition. Statistics in Medicine. 28(19). 2435–2450. 6 indexed citations
15.
Alfò, Marco, Luciano Nieddu, & Donatella Vicari. (2009). Finite Mixture Models for Mapping Spatially Dependent Disease Counts. Biometrical Journal. 51(1). 84–97. 14 indexed citations
16.
Martella, Francesca, Marco Alfò, & Maurizio Vichi. (2008). Biclustering of Gene Expression Data by an Extension of Mixtures of Factor Analyzers. The International Journal of Biostatistics. 4(1). Article 3–Article 3. 16 indexed citations
17.
Sanctis, Vitaliana De, Erica Finolezzi, Mattia Falchetto Osti, et al.. (2008). MACOP-B and Involved-Field Radiotherapy Is an Effective and Safe Therapy for Primary Mediastinal Large B Cell Lymphoma. International Journal of Radiation Oncology*Biology*Physics. 72(4). 1154–1160. 29 indexed citations
18.
Alfò, Marco & Murray Aitkin. (2006). Variance component models for longitudinal count data with baseline information: epilepsy data revisited. Statistics and Computing. 16(3). 231–238. 11 indexed citations
19.
Sanctis, Vitaliana De, Mattia Falchetto Osti, Maurizio Valeriani, et al.. (2006). Radiotherapy and sequential temozolomide compared with radiotherapy with concomitant and sequential temozolomide in the treatment of newly diagnosed glioblastoma multiforme. Anti-Cancer Drugs. 17(8). 969–975. 14 indexed citations
20.
Attorre, Fabio, et al.. (2003). Appendix EA4-2. Community Ecology. 4(1). 43–49. 1 indexed citations

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.

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