Large rank-based models with common noise
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DOI: 10.1016/j.spl.2019.03.005
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- Jianqing Fan & Yuan Liao & Han Liu, 2016. "An overview of the estimation of large covariance and precision matrices," Econometrics Journal, Royal Economic Society, vol. 19(1), pages 1-32, February.
- Gess, Benjamin & Souganidis, Panagiotis E., 2017. "Stochastic non-isotropic degenerate parabolic–hyperbolic equations," Stochastic Processes and their Applications, Elsevier, vol. 127(9), pages 2961-3004.
- B. Jourdain, 2000. "Diffusion Processes Associated with Nonlinear Evolution Equations for Signed Measures," Methodology and Computing in Applied Probability, Springer, vol. 2(1), pages 69-91, April.
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Cited by:
- Mykhaylo Shkolnikov & Lane Chun Yeung, 2024. "From rank-based models with common noise to pathwise entropy solutions of SPDEs," Papers 2406.07286, arXiv.org.
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Keywords
Competing Brownian particles; Porous medium equation; Weak convergence; Wasserstein distance; Empirical measure;All these keywords.
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