most citedNonparametric Density Estimation for Data Scattered on Irregular Spatial Domains: A Likelihood-Based Approach Using Bivariate Penalized Spline Smoothing

1 citations · 1 across the 4 of their papers we have counts for

collaborators
Showing stat.MEShow all

3 papers · 1 filter

stat.ME2024★ 1 cited

Nonparametric Density Estimation for Data Scattered on Irregular Spatial Domains: A Likelihood-Based Approach Using Bivariate Penalized Spline Smoothing

Kunal Das, Shan Yu, Guannan Wang +1

Accurately estimating data density is crucial for making informed decisions and modeling in various fields. This paper presents a novel nonparametric density estimation procedure t…

stat.ME2024

Spatial Heterogeneous Additive Partial Linear Model: A Joint Approach of Bivariate Spline and Forest Lasso

Xin Zhang, Shan Yu, Zhengyuan Zhu +1

Identifying spatial heterogeneous patterns has attracted a surge of research interest in recent years, due to its important applications in various scientific and engineering field…

stat.ME2024

TSSS: A Novel Triangulated Spherical Spline Smoothing for Surface-based Data

Zhiling Gu, Shan Yu, Guannan Wang +2

Surface-based data is commonly observed in diverse practical applications spanning various fields. In this paper, we introduce a novel nonparametric method to discover the underlyi…