Conditional functional clustering for longitudinal data with heterogeneous nonlinear patterns

DOI10.1214/21-AOAS1542zbMath1498.62264MaRDI QIDQ2154229

Lei Yu, Tianhao Wang, Robert S. Wilson, Sue E. Leurgans, David A. Bennett, Patricia A. Boyle

Publication date: 14 July 2022

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

zbMATH Keywords

latent classescohort studyfunctional mixed-effects modelpenalized B-splinesmixture Gaussian processesROSMAP studies

Mathematics Subject Classification ID

Nonparametric regression and quantile regression (62G08) Functional data analysis (62R10) Classification and discrimination; cluster analysis (statistical aspects) (62H30) Applications of statistics to biology and medical sciences; meta analysis (62P10)

Cites Work

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• Gaussian parsimonious clustering models with covariates and a noise component
• Functional clustering in nested designs: modeling variability in reproductive epidemiology studies
• Distance-based clustering of sparsely observed stochastic processes, with applications to online auctions
• A comparison of GCV and GML for choosing the smoothing parameter in the generalized spline smoothing problem
• Estimating the dimension of a model
• Flexible smoothing with \(B\)-splines and penalties. With comments and a rejoinder by the authors
• Clustering longitudinal profiles using P-splines and mixed effects models applied to time-course gene expression data
• Model-based clustering for multivariate functional data
• Cluster analysis of longitudinal profiles with subgroups
• Functional data analysis.
• Optimal smoothing in nonparametric mixed-effect models
• Nonparametric Mixed Effects Models for Unequally Sampled Noisy Curves
• Functional Mixed Effects Models
• A Penalized Spline Approach to Functional Mixed Effects Model Analysis
• A Linear Mixed-Effects Model With Heterogeneity in the Random-Effects Population
• Functional mixture regression
• Mixture Densities, Maximum Likelihood and the EM Algorithm
• Wavelet-based Functional Mixed Models
• Penalized Clustering of Large-Scale Functional Data With Multiple Covariates
• Smoothing Spline Models with Correlated Random Errors
• Best Linear Unbiased Estimation and Prediction under a Selection Model
• Unsupervised Curve Clustering using B‐Splines
• Model-Based Clustering, Discriminant Analysis, and Density Estimation
• Clustering for Sparsely Sampled Functional Data
• Mixed-Effects Models in S and S-PLUS
• Cluster analysis of gene expression dynamics
• An Analysis of Paediatric CD4 Counts for Acquired Immune Deficiency Syndrome Using Flexible Random Curves
• Functional Clustering and Identifying Substructures of Longitudinal Data
• Clustering Functional Data into Groups by Using Projections
• A Nonlinear Model with Latent Process for Cognitive Evolution Using Multivariate Longitudinal Data
• Penalized Likelihood Functional Regression
• Bayesian information criteria and smoothing parameter selection in radial basis function networks
• The Clustering of Regression Models Method with Applications in Gene Expression Data
• Identification in Parametric Models
• Stable and Efficient Multiple Smoothing Parameter Estimation for Generalized Additive Models
• Functional Adaptive Model Estimation
• CATS
• A Quantitative Study of Gene Regulation Involved in the Immune Response of Anopheline Mosquitoes