Jérôme Saracco

1.8k citations
74 papers · 959 indexed · h-index 18
Topics
Statistical Methods and Inference (34 papers)Advanced Statistical Methods and Models (20 papers)Bayesian Methods and Mixture Models (10 papers)
Journals
SHILAP Revista de lepidopterologíaScientific ReportsStatistics in Medicine

In The Last Decade

Jérôme Saracco

72 papers receiving 916 citations

Peers

Jérôme Saracco
Comparison fields: 5 of 169
  • Statistics and Probability 302
  • Artificial Intelligence 174
  • Cognitive Neuroscience 86
  • Molecular Biology 69
  • Animal Science and Zoology 67
Replace G. K. Robinson with:
G. K. Robinson Australia
Eva Cantoni Switzerland
Ana‐Maria Staicu United States
Mark C. K. Yang United States
John I. Marden United States
Fabian Scheipl Germany
Geurt Jongbloed Netherlands
Vicente Núñez‐Antón Spain
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Citations per field
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G. K. Robinson · 1×
Citations per year

Countries citing papers authored by Jérôme Saracco

Since Specialization
Citations

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

Fields of papers citing papers by Jérôme Saracco

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Jérôme Saracco

This figure shows the co-authorship network connecting the top 25 collaborators of Jérôme Saracco. A scholar is included among the top collaborators of Jérôme Saracco 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 Jérôme Saracco. Jérôme Saracco 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
#WorkIndexed citations
1 4
2 16
3 38
4 50
5 87
6 13
7 2
8 1
9 9
10 3
11
Clustering of categorical variables around latent variables
3
12
Estimation de quantiles géométriques conditionnels et non conditionnels
5
13 18
14 13
15 27
16 2
17
Trois méthodes non paramétriques pour l'estimation de courbes de référence-Application à l'analyse de propriétés biophysiques de la peau
1
18 44
19 19
20 21

About Jérôme Saracco

Jérôme Saracco is a scholar working on Statistics and Probability, Animal Science and Zoology and Statistics, Probability and Uncertainty, having authored 74 papers that have together received 959 indexed citations. Recurring topics across this work include Statistical Methods and Inference (34 papers), Advanced Statistical Methods and Models (20 papers) and Bayesian Methods and Mixture Models (10 papers). The work is most often cited by research in Statistics and Probability (302 citations), Animal Science and Zoology (67 citations) and Statistics, Probability and Uncertainty (40 citations). Jérôme Saracco has collaborated with scholars based in France, United States and United Kingdom. Frequent co-authors include Marie Chavent, Vanessa Kuentz-Simonet, Ali Gannoun, Benoît Liquet, Stéphane Girard, Amaury Labenne, Keming Yu, Christiane Guinot, Robin Genuer and George E. Bonney. Their work appears in journals such as SHILAP Revista de lepidopterología, Scientific Reports and Statistics in Medicine.

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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