Pierre Ribereau

403 total citations
20 papers, 197 citations indexed

About

Pierre Ribereau is a scholar working on Finance, Global and Planetary Change and Statistics and Probability. According to data from OpenAlex, Pierre Ribereau has authored 20 papers receiving a total of 197 indexed citations (citations by other indexed papers that have themselves been cited), including 12 papers in Finance, 12 papers in Global and Planetary Change and 7 papers in Statistics and Probability. Recurrent topics in Pierre Ribereau's work include Financial Risk and Volatility Modeling (12 papers), Hydrology and Drought Analysis (10 papers) and Statistical Methods and Inference (6 papers). Pierre Ribereau is often cited by papers focused on Financial Risk and Volatility Modeling (12 papers), Hydrology and Drought Analysis (10 papers) and Statistical Methods and Inference (6 papers). Pierre Ribereau collaborates with scholars based in France, Iraq and Canada. Pierre Ribereau's co-authors include Philippe Naveau, Alexis Hannart, Raphaël Huser, Armelle Guillou, Pascal Yiou, Rudolf Brázdil, M. Nogaj, Véronique Maume‐Deschamps, Jean Diebolt and Jean-Noël Bacro and has published in prestigious journals such as Water Resources Research, Advances in Water Resources and Hydrological Sciences Journal.

In The Last Decade

Pierre Ribereau

18 papers receiving 185 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Pierre Ribereau France 7 152 71 47 30 26 20 197
Benjamin D. Youngman United Kingdom 8 168 1.1× 140 2.0× 14 0.3× 10 0.3× 14 0.5× 11 266
W. Feluch Poland 7 354 2.3× 70 1.0× 25 0.5× 18 0.6× 218 8.4× 11 413
Stefan Siegert United Kingdom 9 121 0.8× 103 1.5× 8 0.2× 10 0.3× 6 0.2× 19 167
M. Nogaj France 6 386 2.5× 288 4.1× 28 0.6× 4 0.1× 34 1.3× 7 430
D. L. Fitzgerald Ireland 7 57 0.4× 32 0.5× 14 0.3× 15 0.5× 18 0.7× 11 112
Wu-Ron Hsu United States 9 239 1.6× 262 3.7× 6 0.1× 4 0.1× 16 0.6× 15 352
Svenja Fischer Germany 11 340 2.2× 64 0.9× 9 0.2× 3 0.1× 254 9.8× 39 406
Geraldine Wong Germany 6 332 2.2× 73 1.0× 11 0.2× 2 0.1× 128 4.9× 8 378
J. M. Sloughter United States 4 275 1.8× 260 3.7× 3 0.1× 12 0.4× 65 2.5× 7 365
M. Carmen Casas Spain 8 302 2.0× 175 2.5× 3 0.1× 4 0.1× 58 2.2× 8 331

Countries citing papers authored by Pierre Ribereau

Since Specialization
Citations

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

Fields of papers citing papers by Pierre Ribereau

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Pierre Ribereau

This figure shows the co-authorship network connecting the top 25 collaborators of Pierre Ribereau. A scholar is included among the top collaborators of Pierre Ribereau 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 Pierre Ribereau. Pierre Ribereau 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.
Maume‐Deschamps, Véronique, et al.. (2025). Regionalization of the extremal dependence structure using spectral clustering. Stochastic Environmental Research and Risk Assessment. 39(2). 725–745.
2.
Maume‐Deschamps, Véronique, et al.. (2024). A spatio-temporal model for temporal evolution of spatial extremal dependence. Spatial Statistics. 64. 100860–100860. 1 indexed citations
3.
Maume‐Deschamps, Véronique, et al.. (2021). Semiparametric estimation for space-time max-stable processes: an F-madogram-based approach. Statistical Inference for Stochastic Processes. 24(2). 241–276. 1 indexed citations
4.
Maume‐Deschamps, Véronique, et al.. (2021). Recognizing a spatial extreme dependence structure: A deep learning approach. Environmetrics. 33(4). 7 indexed citations
5.
Maume‐Deschamps, Véronique, et al.. (2019). Fitting spatial max-mixture processes with unknown extremal dependence class: an exploratory analysis tool. Test. 29(2). 479–522. 3 indexed citations
6.
Ribereau, Pierre, et al.. (2019). Bayesian Inference with M-splines on Spectral Measure of Bivariate Extremes. Methodology And Computing In Applied Probability. 21(3). 765–788. 1 indexed citations
7.
Maume‐Deschamps, Véronique, et al.. (2019). Spatial risk measures for max-stable and max-mixture processes. Stochastics. 92(7). 1005–1020. 1 indexed citations
8.
Blanchet‐Scalliet, Christophette, et al.. (2018). Risk assessment using suprema data. Stochastic Environmental Research and Risk Assessment. 32(10). 2839–2848. 2 indexed citations
9.
Naveau, Philippe, Raphaël Huser, Pierre Ribereau, & Alexis Hannart. (2016). Modeling jointly low, moderate, and heavy rainfall intensities without a threshold selection. Water Resources Research. 52(4). 2753–2769. 108 indexed citations
10.
Kortschak, Dominik, Stéphane Loisel, & Pierre Ribereau. (2015). Ruin Problems with Worsening Risks or with Infinite Mean Claims. Stochastic Models. 31(1). 119–152.
11.
Opitz, Thomas, Jean-Noël Bacro, & Pierre Ribereau. (2015). The spectrogram: A threshold-based inferential tool for extremes of stochastic processes. Electronic Journal of Statistics. 9(1). 3 indexed citations
12.
Ribereau, Pierre, et al.. (2015). Skew generalized extreme value distribution: Probability-weighted moments estimation and application to block maxima procedure. Communication in Statistics- Theory and Methods. 45(17). 5037–5052. 6 indexed citations
13.
Cossette, Hélène, et al.. (2012). Climate change and flood risk. 1 indexed citations
14.
Ribereau, Pierre, Philippe Naveau, & Armelle Guillou. (2011). A note of caution when interpreting parameters of the distribution of excesses. Advances in Water Resources. 34(10). 1215–1221. 11 indexed citations
15.
Guillou, Armelle, Philippe Naveau, Jean Diebolt, & Pierre Ribereau. (2008). Return level bounds for discrete and continuous random variables. Test. 18(3). 584–604. 7 indexed citations
16.
Ribereau, Pierre, Armelle Guillou, & Philippe Naveau. (2008). Estimating return levels from maxima of non-stationary random sequences using the Generalized PWM method. Nonlinear processes in geophysics. 15(6). 1033–1039. 12 indexed citations
17.
Diebolt, Jean, Armelle Guillou, & Pierre Ribereau. (2007). Asymptotic Normality of Extreme Quantile Estimators Based on the Peaks-Over-Threshold Approach. Communication in Statistics- Theory and Methods. 36(5). 869–886. 4 indexed citations
18.
Yiou, Pascal, Pierre Ribereau, Philippe Naveau, M. Nogaj, & Rudolf Brázdil. (2006). Statistical analysis of floods in Bohemia (Czech Republic) since 1825. Hydrological Sciences Journal. 51(5). 930–945. 25 indexed citations
19.
Diebolt, Jean, Armelle Guillou, & Pierre Ribereau. (2005). Asymptotic normality of the extreme quantile estimator based on the POT method. Comptes Rendus Mathématique. 341(5). 307–312. 3 indexed citations
20.
Ribereau, Pierre, et al.. (2005). Vitesses de convergence uniforme presque sûre d'estimateurs non-paramétriques de la régression. Comptes Rendus Mathématique. 340(7). 525–528. 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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