Jérôme Saracco

1.8k total citations
74 papers, 959 citations indexed

About

Jérôme Saracco is a scholar working on Statistics and Probability, Artificial Intelligence and Animal Science and Zoology. According to data from OpenAlex, Jérôme Saracco has authored 74 papers receiving a total of 959 indexed citations (citations by other indexed papers that have themselves been cited), including 39 papers in Statistics and Probability, 18 papers in Artificial Intelligence and 8 papers in Animal Science and Zoology. Recurrent topics in Jérôme Saracco's work include Statistical Methods and Inference (34 papers), Advanced Statistical Methods and Models (20 papers) and Bayesian Methods and Mixture Models (10 papers). Jérôme Saracco is often cited by papers focused on Statistical Methods and Inference (34 papers), Advanced Statistical Methods and Models (20 papers) and Bayesian Methods and Mixture Models (10 papers). Jérôme Saracco collaborates with scholars based in France, United States and United Kingdom. Jérôme Saracco's 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 and has published in prestigious journals such as SHILAP Revista de lepidopterología, Scientific Reports and Statistics in Medicine.

In The Last Decade

Jérôme Saracco

72 papers receiving 916 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Jérôme Saracco France 18 302 174 86 69 67 74 959
John I. Marden United States 18 561 1.9× 304 1.7× 33 0.4× 66 1.0× 60 0.9× 45 1.6k
Dieter Rasch Germany 14 239 0.8× 72 0.4× 52 0.6× 48 0.7× 21 0.3× 86 1.1k
Ana‐Maria Staicu United States 19 712 2.4× 265 1.5× 101 1.2× 93 1.3× 16 0.2× 64 1.2k
Cinzia Viroli Italy 16 186 0.6× 336 1.9× 43 0.5× 91 1.3× 15 0.2× 54 743
Vicente Núñez‐Antón Spain 12 363 1.2× 71 0.4× 35 0.4× 47 0.7× 14 0.2× 54 1.1k
Fabian Scheipl Germany 19 497 1.6× 198 1.1× 59 0.7× 163 2.4× 15 0.2× 43 1.8k
G. K. Robinson Australia 13 487 1.6× 161 0.9× 25 0.3× 78 1.1× 43 0.6× 34 1.6k
Mark C. K. Yang United States 24 153 0.5× 183 1.1× 153 1.8× 198 2.9× 13 0.2× 60 1.8k
Geurt Jongbloed Netherlands 20 477 1.6× 212 1.2× 15 0.2× 150 2.2× 16 0.2× 79 1.4k
David B. Hitchcock United States 15 84 0.3× 124 0.7× 19 0.2× 72 1.0× 33 0.5× 49 938

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
1.
Saracco, Jérôme, M.M. Campo, R.I. Richardson, et al.. (2024). Modelling the physiological, muscular, and sensory characteristics in relation to beef quality from 15 cattle breeds. Livestock Science. 280. 105395–105395. 4 indexed citations
2.
Ellies‐Oury, Marie‐Pierre, et al.. (2019). Statistical model choice including variable selection based on variable importance: A relevant way for biomarkers selection to predict meat tenderness. Scientific Reports. 9(1). 10014–10014. 16 indexed citations
3.
Chavent, Marie, Vanessa Kuentz-Simonet, Amaury Labenne, & Jérôme Saracco. (2018). ClustGeo: an R package for hierarchical clustering with spatial constraints. Computational Statistics. 33(4). 1799–1822. 87 indexed citations
4.
Joliot, Marc, Jérôme Saracco, Gaël Jobard, et al.. (2018). A SENtence Supramodal Areas AtlaS (SENSAAS) based on multiple task-induced activation mapping and graph analysis of intrinsic connectivity in 144 healthy right-handers. Brain Structure and Function. 224(2). 859–882. 50 indexed citations
5.
Girard, Stéphane & Jérôme Saracco. (2016). Supervised and Unsupervised Classification Using Mixture Models. EAS Publications Series. 77. 69–90. 4 indexed citations
6.
Saracco, Jérôme & Marie Chavent. (2016). Clustering of Variables for Mixed Data. EAS Publications Series. 77. 121–169. 1 indexed citations
7.
Girard, Stéphane & Jérôme Saracco. (2014). An Introduction to Dimension Reduction in Nonparametric Kernel Regression. EAS Publications Series. 66. 167–196. 2 indexed citations
8.
Gégout‐Petit, Anne, et al.. (2013). Maintenance Optimisation of Optronic Equipment. SHILAP Revista de lepidopterología. 1 indexed citations
9.
Durrieu, Gilles, et al.. (2013). Comparison of Kernel Density Estimators with Assumption on Number of Modes. Communications in Statistics - Simulation and Computation. 44(1). 196–216. 9 indexed citations
10.
Saracco, Jérôme, et al.. (2010). Clustering of categorical variables around latent variables. RePEc: Research Papers in Economics. 3 indexed citations
11.
Chaouch, Mohamed, Ali Gannoun, & Jérôme Saracco. (2009). Estimation de quantiles géométriques conditionnels et non conditionnels. French digital mathematics library (Numdam). 150(2). 1–27. 5 indexed citations
12.
Saracco, Jérôme, et al.. (2009). Cluster-based Sliced Inverse Regression. Journal of the Korean Statistical Society. 39(2). 251–267. 2 indexed citations
13.
Liquet, Benoît, Jérôme Saracco, & Daniel Commenges. (2007). Selection between proportional and stratified hazards models based on expected log-likelihood. Computational Statistics. 22(4). 619–634. 1 indexed citations
14.
Gannoun, Ali, et al.. (2006). Some extensions of multivariate sliced inverse regression. Journal of Statistical Computation and Simulation. 77(1). 1–17. 18 indexed citations
15.
Menut, Chantal, et al.. (2006). Intraspecific chemical variability and highlighting of chemotypes of leaf essential oils from Ravensara aromatica Sonnerat, a tree endemic to Madagascar. Flavour and Fragrance Journal. 21(5). 833–838. 13 indexed citations
16.
Saracco, Jérôme. (2004). Asymptotics for pooled marginal slicing estimator based on SIRα approach. Journal of Multivariate Analysis. 96(1). 117–135. 27 indexed citations
17.
Gannoun, Ali, Jérôme Saracco, Ao Yuan, & George E. Bonney. (2003). On Adaptive Transformation–Retransformation Estimate of Conditional Spatial Median. Communication in Statistics- Theory and Methods. 32(10). 1981–2011. 2 indexed citations
18.
Gannoun, Ali, Stéphane Girard, Christiane Guinot, & Jérôme Saracco. (2002). Reference curves based on non‐parametric quantile regression. Statistics in Medicine. 21(20). 3119–3135. 44 indexed citations
19.
Gannoun, Ali, Stéphane Girard, Christiane Guinot, & Jérôme Saracco. (2002). Trois méthodes non paramétriques pour l'estimation de courbes de référence-Application à l'analyse de propriétés biophysiques de la peau. French digital mathematics library (Numdam). 50(1). 65–89. 1 indexed citations
20.
Saracco, Jérôme. (2001). POOLED SLICING METHODS VERSUS SLICING METHODS. Communications in Statistics - Simulation and Computation. 30(3). 489–511. 19 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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