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A Central Limit Theorem for Intrinsic Fr\'echet Means on Real Grassmannians
arXiv stat.TH0 views
arXiv:2610.24159v1 Announce Type: cross Abstract: Subspace-valued data arise in dimension reduction, image-set and video recognition, and signal processing, and the Fr\'echet mean is their standard sample mean [11,9,15,23]. We establish a central limit theorem for the intrinsic sample Fr\'echet mean of i.i.d. observations on the real Grassmann manifold $\mathrm{Gr}(p,n)$, as a specialization of the general theorem of [18]. Unlike prior results which require the distribution to vanish or place negligible mass near the cut locus of the population mean, we allow a continuous, possibly positive density. To enable our results, we derive two properties of $\mathrm{Gr}(p,n)$: the first is that the union of the cut loci of all points within distance $\delta$ of the mean has volume $O(\delta)$. The second is that the Hessian of the squared distance function is integrable. We also give a smooth density on $\mathrm{Gr}(1,2)$ for which the mean is unique but the Fr\'echet Hessian vanishes.
Source:https://arxiv.org/abs/2610.24159PreviousInconsistency between Frequentist and Bayesian inference, approximation of improper priors and permissible priorsNextMargin Certificates for Voting Classifiers under Mixing Dependence
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