157 citations · 261 across the 9 of their papers we have counts for
10 papers
A unified framework on defining depth for point process using function smoothing
Zishen Xu, Chenran Wang, Wei Wu
The notion of statistical depth has been extensively studied in multivariate and functional data over the past few decades. In contrast, the depth on temporal point process is stil…
Model-based Statistical Depth with Applications to Functional Data
Weilong Zhao, Zishen Xu, Yun Yang +1
Statistical depth, a commonly used analytic tool in non-parametric statistics, has been extensively studied for multivariate and functional observations over the past few decades.…
Intensity Estimation for Poisson Process with Compositional Noise
Glenna Schluck, Wei Wu, Anuj Srivastava
Intensity estimation for Poisson processes is a classical problem and has been extensively studied over the past few decades. Practical observations, however, often contain composi…
Dirichlet Depths for Point Process
Kai Qi, Yang Chen, Wei Wu
Statistical depths have been well studied for multivariate and functional data over the past few decades, but remain under-explored for point processes. A first attempt on the noti…
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…
Nonparametric Spherical Regression Using Diffeomorphic Mappings
Michael Rosenthal, Wei Wu, Eric Klassen +1
Spherical regression explores relationships between variables on spherical domains. We develop a nonparametric model that uses a diffeomorphic map from a sphere to itself. The rest…