Modelling Sparse Generalized Longitudinal Observations with Latent Gaussian Processes
From MaRDI portal
Publication:3631468
DOI10.1111/j.1467-9868.2008.00656.xOpenAlexW2136261709MaRDI QIDQ3631468
Hall, Peter, Fang Yao, Hans-Georg Müller
Publication date: 10 June 2009
Published in: Journal of the Royal Statistical Society Series B: Statistical Methodology (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1111/j.1467-9868.2008.00656.x
predictionsmoothingstochastic processeigenfunctionrepeated measurementsfunctional data analysisrandom effectfunctional principal componentbinomial data
Related Items
Functional principal component analysis in age–period–cohort analysis of body mass index data by gender and ethnicity, Coherent mortality forecasting by the weighted multilevel functional principal component approach, Rejoinder on: ``Probability enhanced effective dimension reduction for classifying sparse functional data, Ordinal probit functional outcome regression with application to computer-use behavior in rhesus monkeys, Generalized functional additive mixed models, Unnamed Item, Generalized multilevel function‐on‐scalar regression and principal component analysis, Linear mixed function‐on‐function regression models, Hierarchical functional data with mixed continuous and binary measurements, Boosting functional response models for location, scale and shape with an application to bacterial competition, A note on modeling sparse exponential-family functional response curves, Fast symmetric additive covariance smoothing, A New Functional Estimation Procedure for Varying Coefficient Models, Fast Univariate Inference for Longitudinal Functional Models, Extended \(t\)-process regression models, Nonnegative decomposition of functional count data, Dynamic relations for sparsely sampled Gaussian processes, Rejoinder to: Dynamic relations for sparsely sampled Gaussian processes, Cluster non‐Gaussian functional data, Growth dynamics and heritability for plant high‐throughput phenotyping studies using hierarchical functional data analysis, Asymptotic normality for kernel weighted averages estimation, Classification of social media users with generalized functional data analysis, Joint modeling of longitudinal drug using pattern and time to first relapse in cocaine dependence treatment data, Longitudinal functional principal component analysis, Dependent functional data, Empirical Dynamics and Functional Data Analysis, Fast methods for spatially correlated multilevel functional data, Multilevel Cross‐Dependent Binary Longitudinal Data, Inverse regression for longitudinal data, Longitudinal high-dimensional principal components analysis with application to diffusion tensor imaging of multiple sclerosis, Estimation of a rank-reduced functional-coefficient panel data model with serial correlation, Robust functional principal component analysis for non-Gaussian longitudinal data, Functional principal component analysis estimator for non-Gaussian data, Nonparametric estimation of a latent variable model, A Bayesian latent variable approach to functional principal components analysis with binary and count data, A nonparametric spatial test to identify factors that shape a microbiome, Nested Hierarchical Functional Data Modeling and Inference for the Analysis of Functional Plant Phenotypes, Multivariate varying coefficient model for functional responses, Isotone additive latent variable models, Multilevel functional principal component analysis, Covariance function versus covariance matrix estimation in efficient semi-parametric regression for longitudinal data analysis, Generalized Gaussian Process Regression Model for Non-Gaussian Functional Data, Functional Principal Component Analysis of Spatiotemporal Point Processes With Applications in Disease Surveillance, From multivariate to functional data analysis: fundamentals, recent developments, and emerging areas, Efficient semiparametric regression for longitudinal data with regularised estimation of error covariance function, Analysis of multivariate non-Gaussian functional data: a semiparametric latent process approach, Efficient Estimation of the Nonparametric Mean and Covariance Functions for Longitudinal and Sparse Functional Data, Sparse logistic functional principal component analysis for binary data
Uses Software
Cites Work
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- A quantitative genetic model for growth, shape, reaction norms, and other infinite-dimensional characters
- Kernel-based functional principal components
- Applied functional data analysis. Methods and case studies
- Local linear regression smoothers and their minimax efficiencies
- Functional data analysis.
- Misspecified maximum likelihood estimates and generalised linear mixed models
- Shrinkage Estimation for Functional Principal Component Scores with Application to the Population Kinetics of Plasma Folate
- Finite-Sample Variance of Local Polynomials: Analysis and Solutions
- Model-Based Geostatistics
- Analysing longitudinal count data with overdispersion
- Clustering for Sparsely Sampled Functional Data
- Maximum likelihood estimation of generalised linear models for multivariate normal covariance matrix
- Nonparametric Regression Analysis of Longitudinal Data
- Marginally Specified Logistic‐Normal Models for Longitudinal Binary Data
- An Analysis of Paediatric CD4 Counts for Acquired Immune Deficiency Syndrome Using Flexible Random Curves
- A Nonlinear Model with Latent Process for Cognitive Evolution Using Multivariate Longitudinal Data
- Estimated Estimating Equations: Semiparametric Inference for Clustered and Longitudinal Data
- Functional Data Analysis for Sparse Longitudinal Data