23 citations · 26 across the 5 of their papers we have counts for
5 papers · 1 filter
Data-Driven, Soft Alignment of Functional Data Using Shapes and Landmarks
Xiaoyang Guo, Wei Wu, Anuj Srivastava
Alignment or registration of functions is a fundamental problem in statistical analysis of functions and shapes. While there are several approaches available, a more recent approac…
Regression Models Using Shapes of Functions as Predictors
Kyungmin Ahn, J. Derek Tucker, Wei Wu +1
Functional variables are often used as predictors in regression problems. A commonly-used parametric approach, called {\it scalar-on-function regression}, uses the $\ltwo$ inner pr…
Robust Comparison of Kernel Densities on Spherical Domains
Zhengwu Zhang, Eric Klassen, Anuj Srivastava
While spherical data arises in many contexts, including in directional statistics, the current tools for density estimation and population comparison on spheres are quite limited.…
Shape-Constrained Univariate Density Estimation
Sutanoy Dasgupta, Debdeep Pati, Ian H. Jermyn +1
While the problem of estimating a probability density function (pdf) from its observations is classical, the estimation under additional shape constraints is both important and cha…
Phase-Amplitude Separation and Modeling of Spherical Trajectories
Zhengwu Zhang, Eric Klassen, Anuj Srivastava
This paper studies the problem of separating phase-amplitude components in sample paths of a spherical process (longitudinal data on a unit two-sphere). Such separation is essentia…