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math.ST2018
Intrinsic Riemannian Functional Data Analysis
Zhenhua Lin, Fang Yao
In this work we develop a novel and foundational framework for analyzing general Riemannian functional data, in particular a new development of tensor Hilbert spaces along curves o…
math.ST2018
Bootstrapping Max Statistics in High Dimensions: Near-Parametric Rates Under Weak Variance Decay and Application to Functional and Multinomial Data
Miles E. Lopes, Zhenhua Lin, Hans-Georg Mueller
In recent years, bootstrap methods have drawn attention for their ability to approximate the laws of "max statistics" in high-dimensional problems. A leading example of such a stat…