Analysis of multivariate longitudinal data using dynamic lasso-regularized copula models with application to large pediatric cardiovascular studies

DOI10.1080/02664763.2021.1937581zbMath1518.62014OpenAlexW3169496182MaRDI QIDQ6157140

Qizhai Li, Wu, Colin O., Wei Zhang, Xiaoyang Ma, Xin Tian

Publication date: 19 June 2023

Published in: Journal of Applied Statistics (Search for Journal in Brave)

Full work available at URL: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9930767

zbMATH Keywords

multivariate longitudinal datafunctional parameterstatistical machine learningtime-varying covariatedynamic copula modelLasso-regularized spline estimator

Mathematics Subject Classification ID

Ridge regression; shrinkage estimators (Lasso) (62J07) Applications of statistics to biology and medical sciences; meta analysis (62P10) Characterization and structure theory for multivariate probability distributions; copulas (62H05)

Related Items (1)

Editorial to the special issue: Statistical Approaches for Big Data and Machine Learning

Cites Work

• Unnamed Item
• Unnamed Item
• Nonparametric estimation of conditional distribution functions with longitudinal data and time-varying parametric models
• A cross-validation bandwidth choice for kernel density estimates with selection biased data
• Time-varying copula models for longitudinal data
• Models for discrete longitudinal data.
• Nonparametric Estimation of Conditional Distributions and Rank-Tracking Probabilities With Time-Varying Transformation Models in Longitudinal Studies
• Dependence Modeling with Copulas
• Reducing variability of crossvalidation for smoothing-parameter choice
• One-Sided Cross-Validation
• Multivariate Dispersion Models Generated From Gaussian Copula
• COPULA-BASED QUANTILE REGRESSION FOR LONGITUDINAL DATA
• Nonparametric estimation for time-varying transformation models with longitudinal data
• Variable Selection in Nonparametric Varying-Coefficient Models for Analysis of Repeated Measurements
• Linear mixed models for longitudinal data

This page was built for publication: Analysis of multivariate longitudinal data using dynamic lasso-regularized copula models with application to large pediatric cardiovascular studies