Walter Racugno

38 total papers · 644 total citations
24 papers, 435 citations indexed

About

Walter Racugno is a scholar working on Statistics and Probability, Statistics, Probability and Uncertainty and Artificial Intelligence. According to data from OpenAlex, Walter Racugno has authored 24 papers receiving a total of 435 indexed citations (citations by other indexed papers that have themselves been cited), including 21 papers in Statistics and Probability, 4 papers in Statistics, Probability and Uncertainty and 3 papers in Artificial Intelligence. Recurrent topics in Walter Racugno's work include Statistical Methods and Bayesian Inference (17 papers), Advanced Statistical Methods and Models (13 papers) and Statistical Distribution Estimation and Applications (9 papers). Walter Racugno is often cited by papers focused on Statistical Methods and Bayesian Inference (17 papers), Advanced Statistical Methods and Models (13 papers) and Statistical Distribution Estimation and Applications (9 papers). Walter Racugno collaborates with scholars based in Italy, Spain and India. Walter Racugno's co-authors include Laura Ventura, Elı́as Moreno, Luca Greco, Francesco Pauli, Alessandra Salvan, Stefano Cabras, Paolo Girardi, Monica Musio and Nicola Sartori and has published in prestigious journals such as Journal of the American Statistical Association, American Mathematical Monthly and Computational Statistics & Data Analysis.

In The Last Decade

Walter Racugno

22 papers receiving 409 citations

Author Peers

Peers are selected by citation overlap in the author's most active subfields. citations · hero ref

Author						Papers	Cites
Walter Racugno	364	110	90	58	25	24	435
Henrick J. Malik	201 0.6×	66 0.6×	80 0.9×	52 0.9×	23 0.9×	19	391
Stephen G. Walker	292 0.8×	185 1.7×	36 0.4×	51 0.9×	41 1.6×	38	447
H. W. Peers	423 1.2×	126 1.1×	83 0.9×	41 0.7×	30 1.2×	11	489
Takemi Yanagimoto	300 0.8×	118 1.1×	40 0.4×	103 1.8×	30 1.2×	61	451
G.P. Steck	218 0.6×	118 1.1×	57 0.6×	84 1.4×	13 0.5×	26	421
J. Miguel Marín	187 0.5×	101 0.9×	30 0.3×	29 0.5×	32 1.3×	26	408
Joan del Castillo	182 0.5×	74 0.7×	57 0.6×	29 0.5×	55 2.2×	32	397
Olaf Bunke	185 0.5×	50 0.5×	45 0.5×	61 1.1×	34 1.4×	33	399
M. B. Rajarshi	268 0.7×	77 0.7×	124 1.4×	42 0.7×	26 1.0×	31	392
Miguel A. Gómez–Villegas	247 0.7×	109 1.0×	70 0.8×	35 0.6×	22 0.9×	30	377

Countries citing papers authored by Walter Racugno

Since Specialization

Citations

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

Fields of papers citing papers by Walter Racugno

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Walter Racugno

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

All Works

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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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