Aldo Corbellini

532 total citations
22 papers, 261 citations indexed

About

Aldo Corbellini is a scholar working on Statistics and Probability, Statistics, Probability and Uncertainty and Management Science and Operations Research. According to data from OpenAlex, Aldo Corbellini has authored 22 papers receiving a total of 261 indexed citations (citations by other indexed papers that have themselves been cited), including 20 papers in Statistics and Probability, 11 papers in Statistics, Probability and Uncertainty and 5 papers in Management Science and Operations Research. Recurrent topics in Aldo Corbellini's work include Advanced Statistical Methods and Models (20 papers), Statistical Methods and Inference (11 papers) and Advanced Statistical Process Monitoring (11 papers). Aldo Corbellini is often cited by papers focused on Advanced Statistical Methods and Models (20 papers), Statistical Methods and Inference (11 papers) and Advanced Statistical Process Monitoring (11 papers). Aldo Corbellini collaborates with scholars based in Italy, United Kingdom and Belgium. Aldo Corbellini's co-authors include Marco Riani, Anthony C. Atkinson, Sergio Zani, Andrea Cerioli, Domenico Perrotta, Marco Magnani, Alessio Farcomeni and Valentin Todorov and has published in prestigious journals such as SHILAP Revista de lepidopterología, Pattern Recognition and Journal of the Royal Statistical Society Series C (Applied Statistics).

In The Last Decade

Aldo Corbellini

20 papers receiving 250 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Aldo Corbellini Italy 8 110 54 49 23 18 22 261
Łukasz Smaga Poland 9 143 1.3× 33 0.6× 56 1.1× 24 1.0× 75 4.2× 50 322
Atila Göktaş Türkiye 9 48 0.4× 23 0.4× 31 0.6× 14 0.6× 7 0.4× 22 324
Chun Yu China 6 109 1.0× 28 0.5× 99 2.0× 29 1.3× 11 0.6× 14 293
Louis Ferré France 9 155 1.4× 21 0.4× 62 1.3× 47 2.0× 32 1.8× 16 319
B. Yu. Lemeshko Russia 10 120 1.1× 36 0.7× 50 1.0× 12 0.5× 10 0.6× 55 247
Luca Greco Italy 9 140 1.3× 54 1.0× 67 1.4× 18 0.8× 13 0.7× 31 277
Tiantian Yang China 8 81 0.7× 51 0.9× 36 0.7× 10 0.4× 11 0.6× 19 281
M. C. Denham United Kingdom 6 80 0.7× 33 0.6× 33 0.7× 23 1.0× 8 0.4× 9 442
Michael D. Conerly United States 10 160 1.5× 152 2.8× 19 0.4× 45 2.0× 37 2.1× 29 321
Sergio Zani Italy 6 37 0.3× 21 0.4× 25 0.5× 5 0.2× 7 0.4× 12 169

Countries citing papers authored by Aldo Corbellini

Since Specialization
Citations

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

Fields of papers citing papers by Aldo Corbellini

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Aldo Corbellini

This figure shows the co-authorship network connecting the top 25 collaborators of Aldo Corbellini. A scholar is included among the top collaborators of Aldo Corbellini 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 Aldo Corbellini. Aldo Corbellini 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.
Atkinson, Anthony C., Marco Riani, Aldo Corbellini, Domenico Perrotta, & Valentin Todorov. (2025). Robust Statistics Through the Monitoring Approach. Springer series in statistics.
3.
Riani, Marco, Anthony C. Atkinson, & Aldo Corbellini. (2023). Robust Transformations for Multiple Regression via Additivity and Variance Stabilization. Journal of Computational and Graphical Statistics. 33(1). 85–100. 2 indexed citations
4.
Riani, Marco, Anthony C. Atkinson, & Aldo Corbellini. (2022). Automatic robust Box–Cox and extended Yeo–Johnson transformations in regression. Statistical Methods & Applications. 32(1). 75–102. 21 indexed citations
5.
Riani, Marco, et al.. (2022). Information Criteria for Outlier Detection Avoiding Arbitrary Significance Levels. Econometrics and Statistics. 29. 189–205. 4 indexed citations
6.
Riani, Marco, et al.. (2022). Robust Correspondence Analysis. Journal of the Royal Statistical Society Series C (Applied Statistics). 71(5). 1381–1401. 4 indexed citations
7.
Atkinson, Anthony C., Marco Riani, & Aldo Corbellini. (2021). The box-cox transformation: review and extensions. London School of Economics and Political Science Research Online (London School of Economics and Political Science). 1 indexed citations
8.
Corbellini, Aldo, et al.. (2021). fsdaSAS: A Package for Robust Regression for Very Large Datasets Including the Batch Forward Search. SHILAP Revista de lepidopterología. 4(2). 327–347. 4 indexed citations
9.
Atkinson, Anthony C., Marco Riani, & Aldo Corbellini. (2021). The Box–Cox Transformation: Review and Extensions. Statistical Science. 36(2). 92 indexed citations
10.
Corbellini, Aldo, et al.. (2020). Tools for Monitoring Robust Regression in SAS IML Studio: S, MM, LTS, LMS and Especially the Forward Search. Joint Research Centre (European Commission). 1 indexed citations
11.
Corbellini, Aldo, et al.. (2020). Labor market analysis through transformations and robust multivariate models. Socio-Economic Planning Sciences. 73. 100826–100826. 2 indexed citations
12.
Riani, Marco, Anthony C. Atkinson, Andrea Cerioli, & Aldo Corbellini. (2019). Comments on: Data science, big data and statistics. Test. 28(2). 349–352. 2 indexed citations
13.
Atkinson, Anthony C., Marco Riani, & Aldo Corbellini. (2019). The Analysis of Transformations for Profit-and-Loss Data. Journal of the Royal Statistical Society Series C (Applied Statistics). 69(2). 251–275. 5 indexed citations
14.
Riani, Marco, Aldo Corbellini, & Anthony C. Atkinson. (2018). The Use of Prior Information in Very Robust Regression for Fraud Detection. International Statistical Review. 86(2). 205–218. 1 indexed citations
15.
Riani, Marco, Anthony C. Atkinson, Andrea Cerioli, & Aldo Corbellini. (2018). Efficient robust methods via monitoring for clustering and multivariate data analysis. Pattern Recognition. 88. 246–260. 11 indexed citations
16.
Cerioli, Andrea, Marco Riani, Anthony C. Atkinson, & Aldo Corbellini. (2018). Rejoinder to the discussion of “The power of monitoring: how to make the most of a contaminated multivariate sample”. Statistical Methods & Applications. 27(4). 661–666. 7 indexed citations
17.
Cerioli, Andrea, Marco Riani, Anthony C. Atkinson, & Aldo Corbellini. (2017). The power of monitoring: how to make the most of a contaminated multivariate sample. Statistical Methods & Applications. 27(4). 559–587. 29 indexed citations
18.
Atkinson, Anthony C., Aldo Corbellini, & Marco Riani. (2017). Robust Bayesian regression with the forward search: theory and data analysis. Test. 26(4). 869–886. 8 indexed citations
19.
Corbellini, Aldo, et al.. (2004). Searching for the optimal smoothing before applying Dynamic Time Warping. IRIS UNIMORE (University of Modena and Reggio Emilia). 47–50. 1 indexed citations
20.
Zani, Sergio, Marco Riani, & Aldo Corbellini. (1999). New methods for ordering multivariate data: an application to the performance of investment funds. Applied Stochastic Models in Business and Industry. 15(4). 485–493. 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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