A Marginal Approach to Reduced-Rank Penalized Spline Smoothing With Application to Multilevel Functional Data

DOI10.1080/01621459.2013.826134zbMath1288.62155OpenAlexW2066718087WikidataQ30748983 ScholiaQ30748983MaRDI QIDQ5406346

Yuanjia Wang, H. Alex Choi, Myunghee Cho Paik, Huaihou Chen

Publication date: 1 April 2014

Published in: Journal of the American Statistical Association (Search for Journal in Brave)

Full work available at URL: http://europepmc.org/articles/pmc3909538

zbMATH Keywords

asymptoticslongitudinal datasemiparametric modelsGEEfunctional regressionsmoothing parameter selection

Mathematics Subject Classification ID

Related Items (5)

A note on modeling sparse exponential-family functional response curves ⋮ An extension of estimating equations to model longitudinal medical cost trajectory with medicare claims data linked to SEER cancer registry ⋮ Asymptotic properties of penalized splines for functional data ⋮ Asymptotics of bivariate penalised splines ⋮ A penalized likelihood method for nonseparable space-time generalized additive models

Uses Software

• SemiPar

Cites Work

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• Bayesian Hierarchical Spatially Correlated Functional Data Analysis with Application to Colon Carcinogenesis
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