Jun Yan

Finance · with Kojadinovic · 2010–2018

A researcher in the Science corpus: 8 papers; trusts 41 researchers and is trusted by 33 researchers here, as inferred from the citation graph.

Subfields

• Finance — 76 citations into it; #992 of 10,518 by trust here, #2,010 by citations
• Statistics and Probability — 59 citations into it; #2,742 of 12,932 by trust here, #4,014 by citations
• Global and Planetary Change — 39 citations into it; #660 of 10,225 by trust here, #4,198 by citations
• Economics and Econometrics — 21 citations into it; #18,901 of 23,481 by trust here, #22,128 by citations
• Management Science and Operations Research — 14 citations into it; #1,182 of 11,946 by trust here, #2,603 by citations
• Artificial Intelligence — 10 citations into it
• Demography — 7 citations into it; #3,099 of 4,236 by trust here, #3,835 by citations
• Environmental Engineering — 5 citations into it

Whom Jun Yan trusts overall

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

1. Christian Genest
2. Ivan Kojadinovic
3. Olivier Scaillet
4. Bruno R'emillard
5. Alan Genz
6. Yoav Benjamini
7. R. Deidda
8. Michael R. Kosorok
9. Michael A. Stephens
10. Joseph P. Romano

Who trusts Jun Yan overall

1. Ivan Kojadinovic
2. G. Salvadori
3. Eike C. Brechmann
4. Claudia Czado
5. F. Serinaldi
6. Carlo De Michele
7. Christian Genest
8. Jean-David Fermanian
9. M. Janga Reddy
10. Mojca Šraj

Papers from Jun Yan's perspective

Ordered by how strongly the researchers Jun Yan trusts endorse each paper. Same corpus, a different order for every researcher.

1. Fonctions de repartition a n dimensions et leurs marges
2. Semiparametric estimation in copula models
3. Everything You Always Wanted to Know about Copula Modeling but Were Afraid to Ask
4. DISTRIBUTION FREE TESTS OF INDEPENDENCE BASED ON THE SAMPLE DISTRIBUTION FUNCTION
5. RANK-BASED INFERENCE FOR BIVARIATE EXTREME-VALUE COPULAS
6. Extremes in Nature : an approach using Copulas
7. An Introduction to Copulas
8. A Nonparametric Test of Serial Independence for Time Series and Residuals
9. Goodness-of-fit tests for copulas: A review and a power study
10. An Introduction to Statistical Modeling of Extreme Values

Their papers

• Modeling Multivariate Distributions with Continuous Margins Using the copula R Package (2010) — 437 citations
• Comparison of three semiparametric methods for estimating dependence parameters in copula models (2010) — 113 citations
• A goodness-of-fit test for bivariate extreme-value copulas (2011) — 96 citations
• FAST LARGE-SAMPLE GOODNESS-OF-FIT TESTS FOR COPULAS (2011) — 119 citations
• Large‐sample tests of extreme‐value dependence for multivariate copulas (2011) — 60 citations
• Automated threshold selection for extreme value analysis via ordered goodness-of-fit tests with adjustment for false discovery rate (2018) — 62 citations
• Goodness‐of‐fit testing based on a weighted bootstrap: A fast large‐sample alternative to the parametric bootstrap (2012) — 52 citations
• Weighted likelihood copula modeling of extreme rainfall events in Connecticut. (2010) — 53 citations