AI & ML
On the asymptotic shape of quantile surfaces
arXiv stat.TH0 views
arXiv:2609.31345v3 Announce Type: replace Abstract: This article is concerned with the asymptotic shape of quantile surfaces, defined as the set of quantiles at a given level $\alpha$ generated by a controlled one-dimensional distribution. Specifically, when the distribution arises as a linear combination of log-normal random variables and the control is a vector of positive coefficients, we prove that quantile surfaces are globally concave in the left tail ($\alpha\to0$) and globally convex in the right tail ($\alpha\to1$). Moreover, these surfaces exhibit asymptotic separation of scale and shape.
Source:https://arxiv.org/abs/2609.31345PreviousPoincar\'e's Inequality on Sliding-Window Occupation Count Kernels and the Optimal Normalized Spectral-Gap ConstantNextMultiscale Sequential Auditing of Quantile Regression with Point Masses
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