Joint modelling of paired sparse functional data using principal components.
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Selecting the Number of Principal Components in Functional Data.A marginal approach to reduced-rank penalized spline smoothing with application to multilevel functional data.Functional analysis of glaucoma data.Hierarchical functional data with mixed continuous and binary measurements.Methods to assess an exercise intervention trial based on 3-level functional data.A Bayesian generalized random regression model for estimating heritability using overdispersed count dataLongitudinal Functional Data AnalysisLongitudinal functional additive model with continuous proportional outcomes for physical activity data.Reduced Rank Mixed Effects Models for Spatially Correlated Hierarchical Functional Data.Semiparametric regression during 2003-2007.Generalized Functional Linear Models with Semiparametric Single-Index Interactions.Longitudinal functional principal component modeling via Stochastic Approximation Monte Carlo.Modeling time-varying effects with generalized and unsynchronized longitudinal data.Decreases in IL-7 levels during antiretroviral treatment of HIV infection suggest a primary mechanism of receptor-mediated clearance.Regression analysis of sparse asynchronous longitudinal dataSemiparametric variance components models for genetic studies with longitudinal phenotypes.A pairwise interaction model for multivariate functional and longitudinal data.A SIMULTANEOUS CONFIDENCE BAND FOR SPARSE LONGITUDINAL REGRESSION.Modeling Bivariate Longitudinal Hormone Profiles by Hierarchical State Space Models.FPCA-based method to select optimal sampling schedules that capture between-subject variability in longitudinal studies.Functional multiple indicators, multiple causes measurement error models.A note on modeling sparse exponential-family functional response curves.Spline Confidence Bands for Functional Derivatives.Three-part joint modeling methods for complex functional data mixed with zero-and-one-inflated proportions and zero-inflated continuous outcomes with skewness.Derivative estimation for longitudinal data analysis: Examining features of blood pressure measured repeatedly during pregnancyA survey of functional principal component analysisFunctional principal component analysis for identifying multivariate patterns and archetypes of growth, and their association with long-term cognitive development
P2860
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P2860
Joint modelling of paired sparse functional data using principal components.
description
2008 nî lūn-bûn
@nan
2008 թուականի Յունուարին հրատարակուած գիտական յօդուած
@hyw
2008 թվականի հունվարին հրատարակված գիտական հոդված
@hy
2008年の論文
@ja
2008年論文
@yue
2008年論文
@zh-hant
2008年論文
@zh-hk
2008年論文
@zh-mo
2008年論文
@zh-tw
2008年论文
@wuu
name
Joint modelling of paired sparse functional data using principal components.
@ast
Joint modelling of paired sparse functional data using principal components.
@en
type
label
Joint modelling of paired sparse functional data using principal components.
@ast
Joint modelling of paired sparse functional data using principal components.
@en
prefLabel
Joint modelling of paired sparse functional data using principal components.
@ast
Joint modelling of paired sparse functional data using principal components.
@en
P2093
P2860
P356
P1433
P1476
Joint modelling of paired sparse functional data using principal components.
@en
P2093
Jianhua Z Huang
Raymond J Carroll
P2860
P304
P356
10.1093/BIOMET/ASN035
P407
P577
2008-01-01T00:00:00Z