Mean and Covariance Matrix Estimation under Heavy Tails
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Updated
May 24, 2023 - R
Mean and Covariance Matrix Estimation under Heavy Tails
LambertW R package: Lambert W x F distributions and Gaussianization for skewed & heavy-tailed data
pylambertw - sklearn interface to analyze and gaussianize heavy-tailed, skewed data
Accuracy and performance benchmark of stable ("fat-tailed") distribution libraries in Python.
Robust Offline Reinforcement Learning with Heavy-Tailed Rewards
Robust estimation using heavy-tailed distributions
Heavy-tailed ESD without gradient noise
multivariate cauchy estimator - a new and robust bayesian state estimation algorithm
Efficiently generate Gaussian stochastic processes with heavy-tailed algebraic correlations.
Adaptive Location and Scale Estimation with Kernel Weighted Averages - Technical Appendix and Supplemental R Code for Pokojovy et al (2024) CSSC Paper
Heavy-Tailed distributions in Variational Autoencoder (VAE)
Stochastc copula models for VaR and CVaR risk assessment
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