2 citations · 3 across the 16 of their papers we have counts for
18 papers · 1 filter
Estimation of Functional Principal Components from Sparse Functional Data
Uche Mbaka, Jiguo Cao, Michelle Carey
Sparse functional data arise when measurements are observed infrequently and at irregular time points for each subject, often in the presence of measurement error. These characteri…
Locally sparse estimation for simultaneous functional quantile regression
Boyi Hu, Jiguo Cao
Motivated by the study of how daily temperature affects soybean yield, this article proposes a simultaneous functional quantile regression (FQR) model featuring a locally sparse bi…
Convolution-smoothing based locally sparse estimation for functional quantile regression
Hua Liu, Boyi Hu, Jinhong You +1
Motivated by an application to study the impact of temperature, precipitation and irrigation on soybean yield, this article proposes a sparse semi-parametric functional quantile mo…
Two Sample Testing for High-dimensional Functional Data: A Multi-resolution Projection Method
Shouxia Wang, Jiguo Cao, Hua Liu +2
It is of great interest to test the equality of the means in two samples of functional data. Past research has predominantly concentrated on low-dimensional functional data, a focu…
Online Learning of Functional Principal Component Analysis for Multidimensional Functional Data
Muye Nanshan, Nan Zhang, Jiguo Cao
Multidimensional functional data streams arise in diverse scientific fields, yet their analysis poses significant challenges. We propose a novel online framework for functional pri…
Similarity-Informed Transfer Learning for Multivariate Functional Censored Quantile Regression
Hua Liu, Jiaqi Men, Shouxia Wang +2
To address the challenge of utilizing patient data from other organ transplant centers (source cohorts) to improve survival time estimation and inference for a target center (targe…