
Causal Inference on Nonlinear Spaces: Distribution Functions and Beyond
Understanding causal relationships is one of the most important goals of...
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Additive Models for Symmetric PositiveDefinite Matrices, Riemannian Manifolds and Lie groups
In this paper an additive regression model for a symmetric positivedefi...
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Intrinsic Riemannian Functional Data Analysis for Sparse Longitudinal Observations
A novel framework is developed to intrinsically analyze sparsely observe...
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Highdimensional MANOVA via Bootstrapping and its Application to Functional and Sparse Count Data
We propose a new approach to the problem of highdimensional multivariat...
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Wasserstein Regression
The analysis of samples of random objects that do not lie in a vector sp...
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Mean and Covariance Estimation for Functional Snippets
We consider estimation of mean and covariance functions of functional sn...
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Riemannian Geometry of Symmetric Positive Definite Matrices via Cholesky Decomposition
We present a new Riemannian metric, termed LogCholesky metric, on the m...
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Modeling Symmetric Positive Definite Matrices with An Application to Functional Brain Connectivity
In neuroscience, functional brain connectivity describes the connectivit...
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Basis Expansions for Functional Snippets
Estimation of mean and covariance functions is fundamental for functiona...
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Analytic Basis Expansions for Functional Snippets
Estimation of mean and covariance functions is fundamental for functiona...
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Total Variation Regularized Fréchet Regression for MetricSpace Valued Data
NonEuclidean data that are indexed with a scalar predictor such as time...
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Modeling Longitudinal Data on Riemannian Manifolds
When considering functional principal component analysis for sparsely ob...
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Intrinsic Riemannian Functional Data Analysis
In this work we develop a novel and foundational framework for analyzing...
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Estimating Historical Functional Linear Models with a Nested Group Bridge Approach
We study a scalaronfunction historical linear regression model which a...
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Bootstrapping Max Statistics in High Dimensions: NearParametric Rates Under Weak Variance Decay and Application to Functional Data Analysis
In recent years, bootstrap methods have drawn attention for their abilit...
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Zhenhua Lin
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