A Note on the Cut-Locus-Corrected Fréchet Mean Central Limit Theorem
Susovan Pal
Abstract
We record two observations concerning HLW24. First, the proof of its Theorem~1 yields the population linearization (13)--(14) at any critical point of the Fréchet function Fμ, under its remaining geometric and measure-theoretic assumptions; neither isolation nor a nonsingular Hessian of Fμ is needed. Second, its Theorem~2 is given a shorter proof by applying the M-estimator theorem [Theorem~5.23, pp.~53--54]vdV98 to negative squared distance in normal coordinates, as opposed to the Donsker argument used there. We verify the pointwise differentiability, local square-integrable Lipschitz bound, second order expansion of population loss, consistency, and empirical maximization hypotheses. The resulting covariance retains the cut-locus correction. The same argument applies to suitably selected local sample Fréchet minima when the population Hessian is positive definite.
Create a lesson
Related papers
Sequential Certification of Partially Identified Product Targets: Information Limits and Adaptive Sampling
Abdallah Skiredj, Abderrahman Skiredj, Amal El Fallah Seghrouchni
A Partial-Matching Proof of the Neyman--Pearson Lemma
Rami V. Tabri
Neyman Orthogonalized Specification Tests for Conditional Tail Index Models
Liuhua Peng, Shuo Li, Xiaojun Song
On Natural Exponential Families with Log-Affine Generalized Variance
Zeyu Cao, Shaosai Huang
Fundamental Limits of Coherent Imaging in The Presence of Atmospheric Turbulence
Songbin Liu, Hanyu Yang, Junren Chen et al.
Regularization vs. Convolution in Kernel-Based Hypothesis Testing
Omar Hagrass, Bharath K. Sriperumbudur