Alessandro Barbiero

474 total citations
46 papers, 267 citations indexed

About

Alessandro Barbiero is a scholar working on Statistics and Probability, Statistics, Probability and Uncertainty and Artificial Intelligence. According to data from OpenAlex, Alessandro Barbiero has authored 46 papers receiving a total of 267 indexed citations (citations by other indexed papers that have themselves been cited), including 33 papers in Statistics and Probability, 16 papers in Statistics, Probability and Uncertainty and 11 papers in Artificial Intelligence. Recurrent topics in Alessandro Barbiero's work include Statistical Distribution Estimation and Applications (24 papers), Probabilistic and Robust Engineering Design (13 papers) and Statistical Methods and Bayesian Inference (11 papers). Alessandro Barbiero is often cited by papers focused on Statistical Distribution Estimation and Applications (24 papers), Probabilistic and Robust Engineering Design (13 papers) and Statistical Methods and Bayesian Inference (11 papers). Alessandro Barbiero collaborates with scholars based in Italy. Alessandro Barbiero's co-authors include Pier Alda Ferrari, Giancarlo Manzi and Paola Annoni and has published in prestigious journals such as SHILAP Revista de lepidopterología, Psychometrika and Annals of Operations Research.

In The Last Decade

Alessandro Barbiero

39 papers receiving 261 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Alessandro Barbiero Italy 10 183 72 63 42 23 46 267
M. M. Abd El‐Raouf Egypt 9 163 0.9× 100 1.4× 38 0.6× 28 0.7× 31 1.3× 44 281
Abbas Pak Iran 12 221 1.2× 136 1.9× 60 1.0× 34 0.8× 23 1.0× 36 333
Guillermo Martínez‐Flórez Colombia 10 274 1.5× 122 1.7× 93 1.5× 23 0.5× 34 1.5× 61 308
Ramy Aldallal Saudi Arabia 10 230 1.3× 115 1.6× 28 0.4× 38 0.9× 49 2.1× 52 302
Mahdi Teimouri Iran 10 215 1.2× 134 1.9× 45 0.7× 17 0.4× 62 2.7× 40 326
Federico J. O'Reilly Mexico 11 213 1.2× 85 1.2× 75 1.2× 39 0.9× 13 0.6× 34 292
E. I. Abdul Sathar India 10 288 1.6× 167 2.3× 47 0.7× 16 0.4× 28 1.2× 54 321
Somesh Kumar India 12 412 2.3× 156 2.2× 112 1.8× 27 0.6× 16 0.7× 81 453
Aisha Fayomi Saudi Arabia 11 237 1.3× 126 1.8× 41 0.7× 41 1.0× 55 2.4× 32 315
S. P. Ahmad India 8 190 1.0× 101 1.4× 41 0.7× 25 0.6× 43 1.9× 57 254

Countries citing papers authored by Alessandro Barbiero

Since Specialization
Citations

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

Fields of papers citing papers by Alessandro Barbiero

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Alessandro Barbiero

This figure shows the co-authorship network connecting the top 25 collaborators of Alessandro Barbiero. A scholar is included among the top collaborators of Alessandro Barbiero 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 Alessandro Barbiero. Alessandro Barbiero 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.
Barbiero, Alessandro. (2024). Maximal point‐polyserial correlation for non‐normal random distributions. British Journal of Mathematical and Statistical Psychology. 78(1). 341–377.
2.
Barbiero, Alessandro, et al.. (2024). Discrete half-logistic distributions with applications in reliability and risk analysis. Annals of Operations Research. 340(1). 27–57. 3 indexed citations
3.
Barbiero, Alessandro. (2021). Inducing a desired value of correlation between two point-scale variables: a two-step procedure using copulas. AStA Advances in Statistical Analysis. 105(2). 307–334. 2 indexed citations
4.
Barbiero, Alessandro, et al.. (2021). A new method for building a discrete analogue to a continuous random variable based on minimization of a distance between distribution functions. IrInSubria (University of Insubria). 338–341. 4 indexed citations
5.
Barbiero, Alessandro, et al.. (2020). A Discrete Analogue of the Half-Logistic Distribution. 2020 International Conference on Decision Aid Sciences and Application (DASA). 64–67. 6 indexed citations
6.
Barbiero, Alessandro, et al.. (2020). Goodman and Kruskal’s Gamma Coefficient for Ordinalized Bivariate Normal Distributions. Psychometrika. 85(4). 905–925. 9 indexed citations
7.
Barbiero, Alessandro. (2018). Properties and inferential issues of a bivariate version of the geometric distribution. Archivio Istituzionale della Ricerca (Universita Degli Studi Di Milano). 27–27. 1 indexed citations
8.
Barbiero, Alessandro. (2018). On Methods of Estimation for the Type II Discrete Weibull Distribution. Iranian Journal of Science and Technology Transactions of Electrical Engineering. 42(4). 501–514.
9.
Barbiero, Alessandro. (2018). A bivariate geometric distribution allowing for positive or negative correlation. Communication in Statistics- Theory and Methods. 48(11). 2842–2861. 5 indexed citations
10.
Barbiero, Alessandro & Pier Alda Ferrari. (2016). An R package for the simulation of correlated discrete variables. Communications in Statistics - Simulation and Computation. 46(7). 5123–5140. 13 indexed citations
11.
Barbiero, Alessandro & Pier Alda Ferrari. (2015). GenOrd: Simulation of ordinal and discrete variables with given correlation matrix and marginal distributions (v. 1.4.0). Archivio Istituzionale della Ricerca (Universita Degli Studi Di Milano). 4 indexed citations
12.
Barbiero, Alessandro. (2014). Data Transformation for Confidence Interval Improvement: An Application to the Estimation of Stress-Strength Model Reliability. Advances in Decision Sciences. 2014. 1–10. 6 indexed citations
13.
Barbiero, Alessandro & Giancarlo Manzi. (2014). SunterSampling : Sunter's sampling design. IRIS Research product catalog (Sapienza University of Rome).
14.
Barbiero, Alessandro, et al.. (2013). Bootstrapping probability-proportional-to-size samples via calibrated empirical population. Journal of Statistical Computation and Simulation. 85(3). 608–620. 8 indexed citations
15.
Barbiero, Alessandro. (2013). An alternative discrete skew Laplace distribution. Statistical Methodology. 16. 47–67. 17 indexed citations
16.
Ferrari, Pier Alda & Alessandro Barbiero. (2012). Simulating Ordinal Data. Multivariate Behavioral Research. 47(4). 566–589. 42 indexed citations
17.
Barbiero, Alessandro. (2011). Interval estimators for reliability: the bivariate normal case. Journal of Applied Statistics. 39(3). 501–512. 15 indexed citations
18.
Barbiero, Alessandro. (2011). Confidence Intervals for Reliability of Stress-Strength Models in the Normal Case. Communications in Statistics - Simulation and Computation. 40(6). 907–925. 14 indexed citations
19.
Barbiero, Alessandro. (2010). A Discretizing Method For Reliability Computation In Complex Stress-Strength Models. Archivio Istituzionale della Ricerca (Universita Degli Studi Di Milano). 4(11). 1395–1401. 2 indexed citations
20.
Barbiero, Alessandro. (2010). Comparing Interval Estimators For Reliability In A Dependent Set-Up. Zenodo (CERN European Organization for Nuclear Research). 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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