User-Friendly Covariance Estimation for Heavy-Tailed Distributions
نویسندگان
چکیده
منابع مشابه
Estimation of the covariance structure of heavy-tailed distributions
We propose and analyze a new estimator of the covariance matrix that admits strong theoretical guarantees under weak assumptions on the underlying distribution, such as existence of moments of only low order. While estimation of covariance matrices corresponding to sub-Gaussian distributions is well-understood, much less in known in the case of heavy-tailed data. As K. Balasubramanian and M. Yu...
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Estimation of High Conditional Quantiles for HeavyTailed Distributions Huixia Judy Wang a , Deyuan Li b & Xuming He c a Department of Statistics , North Carolina State University , Raleigh , NC , 27695 b Department of Statistics , Fudan University , Shanghai , 200433 , China c Department of Statistics , University of Michigan Accepted author version posted online: 12 Sep 2012.Published online: ...
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Combinatorial search methods often exhibit a large variability in performance. We study the cost prooles of combinatorial search procedures. Our study reveals some intriguing properties of such cost prooles. The distributions are often characterized by very long tails or \heavy tails". We will show that these distributions are best characterized by a general class of distributions that have no ...
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In [18], a new family of distributions is introduced, depending on two parameters τ and θ, which encompasses Pareto-type distributions as well as Weibull tail-distributions. Estimators for θ and extreme quantiles are also proposed, but they both depend on the unknown parameter τ , making them useless in practical situations. In this paper, we propose an estimator of τ which is independent of θ....
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ژورنال
عنوان ژورنال: Statistical Science
سال: 2019
ISSN: 0883-4237
DOI: 10.1214/19-sts711