Raffaele Argiento

608 total citations
36 papers, 354 citations indexed

About

Raffaele Argiento is a scholar working on Artificial Intelligence, Statistics and Probability and Molecular Biology. According to data from OpenAlex, Raffaele Argiento has authored 36 papers receiving a total of 354 indexed citations (citations by other indexed papers that have themselves been cited), including 25 papers in Artificial Intelligence, 17 papers in Statistics and Probability and 5 papers in Molecular Biology. Recurrent topics in Raffaele Argiento's work include Bayesian Methods and Mixture Models (23 papers), Statistical Methods and Bayesian Inference (10 papers) and Statistical Methods and Inference (7 papers). Raffaele Argiento is often cited by papers focused on Bayesian Methods and Mixture Models (23 papers), Statistical Methods and Bayesian Inference (10 papers) and Statistical Methods and Inference (7 papers). Raffaele Argiento collaborates with scholars based in Italy, United States and United Kingdom. Raffaele Argiento's co-authors include Alessandra Guglielmi, Antonio Pievatolo, Robin Pemantle, Brian Skyrms, Stanislav Volkov, Marina Vannucci, Maria De Iorio, W. Duncan Wadsworth, Jessica Galloway-Peña and Samuel A. Shelburne and has published in prestigious journals such as Journal of the American Statistical Association, Biometrics and IEEE Transactions on Power Systems.

In The Last Decade

Raffaele Argiento

30 papers receiving 329 citations

Peers

Raffaele Argiento

MSOR

SPS

John W. Lau Australia

Takashi Seo Japan

Zahra Almaspoor Iran

Jelena Bradić United States

Archana Purwar India

Dominik Strzałka Poland

Isha Dewan India

Jingjing Wu Canada

Xuan Bi United States

John W. Lau Australia

Raffaele Argiento

175 ×1.1

103 ×1.0

60 ×1.0

30 ×0.5

MSOR

6 ×0.1

SPS

Citations per year, relative to Raffaele Argiento Raffaele Argiento (= 1×) peers John W. Lau

Countries citing papers authored by Raffaele Argiento

Since Specialization

Citations

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

Fields of papers citing papers by Raffaele Argiento

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Raffaele Argiento

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

All Works

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20 of 20 papers shown

Colombi, A., et al.. (2024). Hierarchical Mixture of Finite Mixtures. Bayesian Analysis. 20(4).

Argiento, Raffaele, et al.. (2024). Personalized treatment selection via product partition models with covariates. Biometrics. 80(1).

Poli, Giovanni, Raffaele Argiento, Amedeo Amedei, & Francesco C. Stingo. (2024). High‐Dimensional Bayesian Semiparametric Models for Small Samples: A Principled Approach to the Analysis of Cytokine Expression Data. Biometrical Journal. 66(8). e70000–e70000.

Argiento, Raffaele, et al.. (2024). Model-Based Clustering of Categorical Data Based on the Hamming Distance. Journal of the American Statistical Association. 120(550). 1178–1188.

Argiento, Raffaele, et al.. (2022). Bayesian GARCH modeling of functional sports data. Statistical Methods & Applications. 32(2). 401–423. 1 indexed citations

Matechou, Eleni & Raffaele Argiento. (2022). Capture-Recapture Models with Heterogeneous Temporary Emigration. Journal of the American Statistical Association. 118(541). 56–69. 1 indexed citations

Argiento, Raffaele, et al.. (2022). Forecasting short-term defaults of firms in a commercial network via Bayesian spatial and spatio-temporal methods. International Journal of Forecasting. 39(3). 1065–1077. 7 indexed citations

Argiento, Raffaele, Maria De Iorio, Shirong Cai, et al.. (2022). Seemingly Unrelated Multi-State Processes: A Bayesian Semiparametric Approach. Bayesian Analysis. 18(3). 2 indexed citations

Argiento, Raffaele, et al.. (2022). New Frontiers in Bayesian Statistics. Springer proceedings in mathematics & statistics. 1 indexed citations

10.

Argiento, Raffaele, et al.. (2021). MCMC Computations for Bayesian Mixture Models Using Repulsive Point Processes. Journal of Computational and Graphical Statistics. 31(2). 422–435. 12 indexed citations

11.

Argiento, Raffaele, et al.. (2019). Hierarchical Normalized Completely Random Measures for Robust Graphical Modeling. Bayesian Analysis. 14(4). 1271–1301. 9 indexed citations

12.

Wadsworth, W. Duncan, Raffaele Argiento, Michele Guindani, et al.. (2017). An integrative Bayesian Dirichlet-multinomial regression model for the analysis of taxonomic abundances in microbiome data. BMC Bioinformatics. 18(1). 185–185. 54 indexed citations

13.

Wang, Charlotte, Fabrizio Ruggeri, Chuhsing Kate Hsiao, & Raffaele Argiento. (2016). Bayesian nonparametric clustering and association studies for candidate SNP observations. International Journal of Approximate Reasoning. 80. 19–35. 1 indexed citations

14.

Argiento, Raffaele, et al.. (2015). Efficient uncertainty quantification in stochastic finite element analysis based on functional principal components. Computational Mechanics. 56(3). 533–549. 5 indexed citations

15.

Argiento, Raffaele, Alessandra Guglielmi, & Antonio Pievatolo. (2013). Estimation, prediction and interpretation of NGG random effects models: an application to Kevlar fibre failure times. Statistical Papers. 55(3). 805–826. 2 indexed citations

16.

Argiento, Raffaele, et al.. (2012). A semiparametric Bayesian generalized linear mixed model for the reliability of Kevlar fibers. Applied Stochastic Models in Business and Industry. 29(5). 410–423. 3 indexed citations

17.

Argiento, Raffaele, Alessandra Guglielmi, & Antonio Pievatolo. (2009). A comparison of nonparametric priors in hierarchical mixture modelling for AFT regression. Journal of Statistical Planning and Inference. 139(12). 3989–4005. 4 indexed citations

18.

Argiento, Raffaele, Robin Pemantle, Brian Skyrms, & Stanislav Volkov. (2008). Learning to signal: Analysis of a micro-level reinforcement model. Stochastic Processes and their Applications. 119(2). 373–390. 73 indexed citations

19.

Argiento, Raffaele, Alessandra Guglielmi, & Antonio Pievatolo. (2008). Nonparametric Bayesian mixture modelling for failure time data. Virtual Community of Pathological Anatomy (University of Castilla La Mancha). 1–19. 3 indexed citations

20.

Argiento, Raffaele, et al.. (2002). Seasonal patterns and double measurement scale in modelling failures in underground trains. 45–48. 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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