Clémentine Prieur

2.7k total citations
61 papers, 1.1k citations indexed

About

Clémentine Prieur is a scholar working on Statistics, Probability and Uncertainty, Statistics and Probability and Finance. According to data from OpenAlex, Clémentine Prieur has authored 61 papers receiving a total of 1.1k indexed citations (citations by other indexed papers that have themselves been cited), including 28 papers in Statistics, Probability and Uncertainty, 17 papers in Statistics and Probability and 16 papers in Finance. Recurrent topics in Clémentine Prieur's work include Probabilistic and Robust Engineering Design (28 papers), Statistical Methods and Inference (12 papers) and Stochastic processes and financial applications (9 papers). Clémentine Prieur is often cited by papers focused on Probabilistic and Robust Engineering Design (28 papers), Statistical Methods and Inference (12 papers) and Stochastic processes and financial applications (9 papers). Clémentine Prieur collaborates with scholars based in France, United States and Venezuela. Clémentine Prieur's co-authors include Jérôme Dedecker, Alexandre Janon, Maëlle Nodet, José R. León, Thierry Klein, Paul Doukhan, Gabriel Lang, Sana Louhichi, Agnès Lagnoux and Anne‐Catherine Favre and has published in prestigious journals such as SHILAP Revista de lepidopterología, Water Resources Research and International Journal for Numerical Methods in Engineering.

In The Last Decade

Clémentine Prieur

55 papers receiving 1.1k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Clémentine Prieur France 16 330 272 251 180 159 61 1.1k
Krzysztof Podgórski Sweden 17 227 0.7× 654 2.4× 507 2.0× 148 0.8× 367 2.3× 82 1.9k
A. J. Lawrance United Kingdom 20 120 0.4× 435 1.6× 288 1.1× 154 0.9× 182 1.1× 72 1.4k
J. M. Angulo Spain 18 99 0.3× 166 0.6× 234 0.9× 167 0.9× 129 0.8× 99 1.1k
Jan Hannig United States 21 322 1.0× 939 3.5× 189 0.8× 85 0.5× 327 2.1× 90 1.6k
Fabrice Gamboa France 19 486 1.5× 247 0.9× 86 0.3× 34 0.2× 160 1.0× 79 1.3k
Juan A. Cuesta‐Albertos Spain 21 218 0.7× 763 2.8× 118 0.5× 56 0.3× 433 2.7× 64 1.5k
M. D. Ruiz‐Medina Spain 18 75 0.2× 199 0.7× 333 1.3× 171 0.9× 118 0.7× 115 1.1k
José A. Dı́az-Garcı́a Mexico 17 123 0.4× 489 1.8× 90 0.4× 85 0.5× 141 0.9× 71 854
Piotr Jaworski Poland 16 80 0.2× 290 1.1× 625 2.5× 119 0.7× 127 0.8× 65 1.1k
N. Balakrishnan Netherlands 8 244 0.7× 510 1.9× 139 0.6× 80 0.4× 209 1.3× 9 1.3k

Countries citing papers authored by Clémentine Prieur

Since Specialization
Citations

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

Fields of papers citing papers by Clémentine Prieur

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Clémentine Prieur

This figure shows the co-authorship network connecting the top 25 collaborators of Clémentine Prieur. A scholar is included among the top collaborators of Clémentine Prieur 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 Clémentine Prieur. Clémentine Prieur 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.
Nouy, Anthony, et al.. (2024). A probabilistic reduced basis method for parameter-dependent problems. Advances in Computational Mathematics. 50(2).
2.
Borgonovo, Emanuele, Elmar Plischke, & Clémentine Prieur. (2024). Total effects with constrained features. Statistics and Computing. 34(2). 1 indexed citations
3.
Helbert, Céline, et al.. (2023). Une version SUR du critère de Bichon pour l'estimation d'un ensemble d'excursion. HAL (Le Centre pour la Communication Scientifique Directe). 11 indexed citations
4.
Nouy, Anthony, et al.. (2022). A PAC algorithm in relative precision for bandit problem with costly sampling. Mathematical Methods of Operations Research. 96(2). 161–185. 1 indexed citations
5.
Favre, Anne‐Catherine, et al.. (2022). Improved Regional Frequency Analysis of rainfall data. Weather and Climate Extremes. 36. 100456–100456. 9 indexed citations
6.
Georges, Didier, et al.. (2022). Spatialized epidemiological forecasting applied to Covid-19 pandemic at departmental scale in France. Systems & Control Letters. 164. 105240–105240.
7.
Prieur, Christophe, et al.. (2020). Transport effect of COVID-19 pandemic in France. Annual Reviews in Control. 50. 394–408. 28 indexed citations
8.
Prieur, Clémentine, et al.. (2019). Global Sensitivity Analysis for Models Described by Stochastic Differential Equations. Methodology And Computing In Applied Probability. 22(2). 803–831. 3 indexed citations
9.
Helbert, Céline, et al.. (2019). Data-driven stochastic inversion via functional quantization. Statistics and Computing. 30(3). 525–541. 6 indexed citations
10.
Arnaud, Élise, et al.. (2018). Making the best use of permutations to compute sensitivity indices with replicated orthogonal arrays. Reliability Engineering & System Safety. 187. 28–39. 5 indexed citations
11.
Comte, Fabienne, Clémentine Prieur, & Adeline Samson. (2017). Adaptive estimation for stochastic damping Hamiltonian systems under partial observation. Stochastic Processes and their Applications. 127(11). 3689–3718. 10 indexed citations
12.
Helbert, Céline, et al.. (2016). Uncertainty quantification for functional dependent random variables. Computational Statistics. 32(2). 559–583. 11 indexed citations
13.
Prieur, Clémentine, et al.. (2015). Replication procedure for grouped Sobol' indices estimation in dependent uncertainty spaces. Information and Inference A Journal of the IMA. iav010–iav010. 2 indexed citations
14.
Bernardino, Éléna Di, Véronique Maume‐Deschamps, & Clémentine Prieur. (2013). Estimating a bivariate tail: A copula based approach. Journal of Multivariate Analysis. 119. 81–100. 6 indexed citations
15.
Cattiaux, Patrick, José R. León, & Clémentine Prieur. (2013). Estimation for stochastic damping hamiltonian systems under partial observation—I. Invariant density. Stochastic Processes and their Applications. 124(3). 1236–1260. 12 indexed citations
16.
Janon, Alexandre, Thierry Klein, Agnès Lagnoux, Maëlle Nodet, & Clémentine Prieur. (2013). Asymptotic normality and efficiency of two Sobol index estimators. ESAIM Probability and Statistics. 18. 342–364. 151 indexed citations
17.
Maume‐Deschamps, Véronique, et al.. (2012). Some multivariate risk indicators: Minimization by using a Kiefer–Wolfowitz approach to the mirror stochastic algorithm. Statistics & Risk Modeling. 29(1). 47–72. 1 indexed citations
18.
Dedecker, Jérôme & Clémentine Prieur. (2006). An empirical central limit theorem for dependent sequences. Stochastic Processes and their Applications. 117(1). 121–142. 29 indexed citations
19.
Prieur, Clémentine, et al.. (2002). Estimation d'une rupture en dépendance faible. Comptes Rendus Mathématique. 335(3). 267–270. 1 indexed citations
20.
Prieur, Clémentine. (2001). Estimation de la densité invariante de systèmes dynamiques en dimension . Comptes Rendus de l Académie des Sciences - Series I - Mathematics. 332(8). 761–764. 2 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.

Explore authors with similar magnitude of impact

Breakdown of academic impact, for papers by Krzysztof Podgórski Breakdown of academic impact, for papers by A. J. Lawrance Breakdown of academic impact, for papers by J. M. Angulo Breakdown of academic impact, for papers by Jan Hannig Breakdown of academic impact, for papers by Fabrice Gamboa Breakdown of academic impact, for papers by Juan A. Cuesta‐Albertos Breakdown of academic impact, for papers by M. D. Ruiz‐Medina Breakdown of academic impact, for papers by José A. Dı́az-Garcı́a Breakdown of academic impact, for papers by Piotr Jaworski Breakdown of academic impact, for papers by N. Balakrishnan
Rankless by CCL
2026