Results 31 to 40 of about 41,863 (267)
Robust Regression with Asymmetric Heavy-Tail Noise Distributions [PDF]
Neural Computation, 2002 In the presence of a heavy-tail noise distribution, regression becomes much more difficult. Traditional robust regression methods assume that the noise distribution is symmetric, and they downweight the influence of so-called outliers. When the noise distribution is asymmetric, these methods yield biased regression estimators. Motivated by data-mining
Yoshua Bengio +2 more
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The Random Effect Transformation for Three Regularity Classes
MathematicsWe continue the analysis of the influence of the random effect transformation on the regularity of distribution functions. The paper considers three regularity classes: heavy-tailed distributions, distributions with consistently varying tails, and ...
Jonas Šiaulys +2 more
doaj +1 more source
Journal of Water and Climate Change, 2021 Daily precipitation extremes are crucial in the hydrological design of major water control structures and are expected to show a changing tendency over time due to climate change.
Neha Gupta, Sagar Rohidas Chavan
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Truncated Moments for Heavy-Tailed and Related Distribution Classes
Mathematics, 2023 Suppose that ξ+ is the positive part of a random variable defined on the probability space (Ω,F,P) with the distribution function Fξ. When the moment Eξ+p of order p>0 is finite, then the truncated moment F¯ξ,p(x)=min1,Eξp1I{ξ>x}, defined for all x⩾0, is
Saulius Paukštys +2 more
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Comparing downside risk measures for heavy tailed distributions [PDF]
Economics Letters, 2006 zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Casper G. de Vries +3 more
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A Parametric Bootstrap for Heavy Tailed Distributions [PDF]
SSRN Electronic Journal, 2011 It is known that Efron’s bootstrap of the mean of a distribution in the domain of attraction of the stable laws with infinite variance is not consistent, in the sense that the limiting distribution of the bootstrap mean is not the same as the limiting distribution of the mean from the real sample. Moreover, the limiting bootstrap distribution is random
Adriana Cornea, Russell Davidson
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Journal of Economic and Financial Sciences, 2019 Orientation: Value-at-risk (VAR) and other risk management tools, such as expected shortfall (conditional VAR), are heavily reliant on a suitable set of underlying distributional conjecture.
Retius Chifurira, Knowledge Chinhamu
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Remote Sensing, 2023 A novel Student’s t-based robust Poisson multi-Bernoulli mixture (PMBM) filter is proposed to effectively perform multi-target tracking under heavy-tailed process and measurement noises.
Jiangbo Zhu, Weixin Xie, Zongxiang Liu
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Sample Covariance Matrices of Heavy-Tailed Distributions [PDF]
International Mathematics Research Notices, 2017 Let $p>2$, $B\geq 1$, $N\geq n$ and let $X$ be a centered $n$-dimensional random vector with the identity covariance matrix such that $\sup\limits_{a\in S^{n-1}}{\mathrm E}|\langle X,a\rangle|^p\leq B$. Further, let $X_1,X_2,\dots,X_N$ be independent copies of $X$, and $ _N:=\frac{1}{N}\sum_{i=1}^N X_i {X_i}^T$ be the sample covariance matrix.
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Structural biology of ferritin nanocages
FEBS Letters, EarlyView.Ferritin is a conserved iron‐storage protein that sequesters iron as a ferric mineral core within a nanocage, protecting cells from oxidative damage and maintaining iron homeostasis. This review discusses ferritin biology, structure, and function, and highlights recent cryo‐EM studies revealing mechanisms of ferritinophagy, cellular iron uptake, and ...
Eloise Mastrangelo, Flavio Di Pisa
wiley +1 more source