Estimation and model selection in generalized additive partial linear models for correlated data with diverging number of covariates
Supplement to “Estimation and model selection in generalized additive partial linear models
for correlated data with diverging number of covariates”. The supplementary material …
for correlated data with diverging number of covariates”. The supplementary material …
Exploration of heterogeneous treatment effects via concave fusion
Understanding treatment heterogeneity is essential to the development of precision
medicine, which seeks to tailor medical treatments to subgroups of patients with similar …
medicine, which seeks to tailor medical treatments to subgroups of patients with similar …
[HTML][HTML] Test of significance for high-dimensional longitudinal data
This paper concerns statistical inference for longitudinal data with ultrahigh dimensional
covariates. We first study the problem of constructing confidence intervals and hypothesis …
covariates. We first study the problem of constructing confidence intervals and hypothesis …
Estimation and inference in semiparametric quantile factor models
We consider a semiparametric quantile factor panel model that allows observed stock-
specific characteristics to affect stock returns in a nonlinear time-varying way, extending …
specific characteristics to affect stock returns in a nonlinear time-varying way, extending …
[HTML][HTML] Consistent variable selection for functional regression models
The dual problem of testing the predictive significance of a particular covariate, and
identification of the set of relevant covariates is common in applied research and …
identification of the set of relevant covariates is common in applied research and …
Efficient estimation of partially linear models for data on complicated domains by bivariate penalized splines over triangulations
In this study, we consider the estimation of partially linear models for spatial data distributed
over complex domains. We use bivariate splines over triangulations to represent the …
over complex domains. We use bivariate splines over triangulations to represent the …
Generalized additive partial linear models for clustered data with diverging number of covariates using GEE
We study flexible modeling of clustered data using marginal generalized additive partial
linear models with a diverging number of covariates. Generalized estimating equations are …
linear models with a diverging number of covariates. Generalized estimating equations are …
A fusion learning method to subgroup analysis of Alzheimer's disease
M Liu, J Yang, Y Liu, B Jia, YF Chen… - Journal of Applied …, 2023 - Taylor & Francis
Uncovering the heterogeneity in the disease progression of Alzheimer's is a key factor to
disease understanding and treatment development, so that interventions can be tailored to …
disease understanding and treatment development, so that interventions can be tailored to …
Penalized variable selection for lipid–environment interactions in a longitudinal lipidomics study
Lipid species are critical components of eukaryotic membranes. They play key roles in many
biological processes such as signal transduction, cell homeostasis, and energy storage …
biological processes such as signal transduction, cell homeostasis, and energy storage …
Two-step spline estimating equations for generalized additive partially linear models with large cluster sizes
S Ma - 2012 - projecteuclid.org
We propose a two-step estimating procedure for generalized additive partially linear models
with clustered data using estimating equations. Our proposed method applies to the case …
with clustered data using estimating equations. Our proposed method applies to the case …