Sparse M-estimators in semi-parametric copula models-Reference-Cited by-同舟云学术

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Sparse M-estimators in semi-parametric copula models

Published:2024-08-01 Issue:3 Volume:30 Page:
ISSN:1350-7265
Container-title:Bernoulli
language:
Short-container-title:Bernoulli

Author:

Fermanian Jean-David¹,Poignard Benjamin²

Affiliation:

1. CREST-Ensae, 5, avenue Henry Le Chatelier, 91120 Palaiseau, France

2. Osaka University, Graduate School of Economics, 1-7, Machikaneyama, Toyonaka-Shi, Osaka-Fu, 560-0043, Japan. Jointly affiliated at RIKEN Center for Advanced Intelligence Project (AIP) and CREST-LFA

Publisher

Bernoulli Society for Mathematical Statistics and Probability

Reference34 articles.

1. Bühlmann, P. and van de Geer, S. (2011). Statistics for High-Dimensional Data: Methods, Theory and Applications. Springer Series in Statistics. Heidelberg: Springer. 10.1007/978-3-642-20192-9

2. Loh, P.-L. and Wainwright, M.J. (2017). Support recovery without incoherence: A case for nonconvex regularization. Ann. Statist. 45 2455–2482. 10.1214/16-AOS1530

3. Berghaus, B., Bücher, A. and Volgushev, S. (2017). Weak convergence of the empirical copula process with respect to weighted metrics. Bernoulli 23 743–772. 10.3150/15-BEJ751

4. Radulović, D., Wegkamp, M. and Zhao, Y. (2017). Weak convergence of empirical copula processes indexed by functions. Bernoulli 23 3346–3384. 10.3150/16-BEJ849

5. Fan, J. and Peng, H. (2004). Nonconcave penalized likelihood with a diverging number of parameters. Ann. Statist. 32 928–961. 10.1214/009053604000000256

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