Anne-Catherine Favre

Finance · 2004–2019

A researcher in the Science corpus: 9 papers; trusts 81 researchers and is trusted by 111 researchers here, as inferred from the citation graph.

Subfields

• Finance — 91 citations into it; #208 of 10,518 by trust here, #362 by citations
• Global and Planetary Change — 69 citations into it; #27 of 10,225 by trust here, #326 by citations
• Statistics and Probability — 56 citations into it; #4,617 of 12,932 by trust here, #2,629 by citations
• Management Science and Operations Research — 23 citations into it
• Economics and Econometrics — 22 citations into it
• Environmental Engineering — 13 citations into it; #47 of 5,479 by trust here, #352 by citations
• Atmospheric Science — 12 citations into it; #3,997 of 4,804 by trust here, #3,694 by citations
• Artificial Intelligence — 11 citations into it

Whom Anne-Catherine Favre trusts overall

Their strongest outbound trust, strongest first, inferred from their citations.

1. Christian Genest
2. G. Salvadori
3. Carlo De Michele
4. Paul Embrechts
5. Jean-David Fermanian
6. Roger B. Nelsen
7. András Bárdossy
8. Thorsten Rheinländer
9. Umberto Cherubini
10. Svetlozar T. Rachev

Who trusts Anne-Catherine Favre overall

1. Songbai Song
2. Vijay P. Singh
3. F. Serinaldi
4. Subimal Ghosh
5. M. Janga Reddy
6. Fabrizio Durante
7. Sander Vandenberghe
8. G. Salvadori
9. Eike C. Brechmann
10. Andrew J. Patton

Papers from Anne-Catherine Favre's perspective

Ordered by how strongly the researchers Anne-Catherine Favre trusts endorse each paper. Same corpus, a different order for every researcher.

1. Risk Management: Correlation and Dependence in Risk Management: Properties and Pitfalls
2. Fonctions de repartition a n dimensions et leurs marges
3. Multivariate hydrological frequency analysis using copulas
4. Risk Management: Value at Risk and Beyond
5. Bivariate Statistical Approach to Check Adequacy of Dam Spillway
6. Asymptotic efficiency of the two-stage estimation method for copula-based models
7. Model Selection and Semiparametric Inference for Bivariate Failure-Time Data
8. An Introduction to Copulas
9. A Generalized Pareto intensity‐duration model of storm rainfall exploiting 2‐Copulas
10. Frequency analysis via copulas: Theoretical aspects and applications to hydrological events

Their papers

• Metaelliptical copulas and their use in frequency analysis of multivariate hydrological data (2007) — 248 citations
• A new rainfall model based on the Neyman‐Scott process using cubic copulas (2008) — 63 citations
• Flexible semiparametric generalized Pareto modeling of the entire range of rainfall amount (2019) — 58 citations
• Modeling the spatial dependence of floods using the Fisher copula (2019) — 66 citations
• Stochastic generation of multi-site daily precipitation focusing on extreme events (2018) — 100 citations
• Importance of Tail Dependence in Bivariate Frequency Analysis (2007) — 185 citations
• Everything You Always Wanted to Know about Copula Modeling but Were Afraid to Ask (2007) — 1,570 citations
• Probabilistic forecasting from ensemble prediction systems: Improving upon the best‐member method by using a different weight and dressing kernel for each member (2006) — 92 citations
• Multivariate hydrological frequency analysis using copulas (2004) — 679 citations