Model selection using modified AIC and BIC in joint modeling of paired functional data

DOI10.1016/J.SPL.2010.08.020zbMath1202.62085OpenAlexW2009328134MaRDI QIDQ613185

Lan Zhou, Jiawei Wei

Publication date: 20 December 2010

Published in: Statistics \& Probability Letters (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.spl.2010.08.020

zbMATH Keywords

AICBICpenalized splinesmixed effects modelfunctional principle components

Mathematics Subject Classification ID

Factor analysis and principal components; correspondence analysis (62H25) Statistical aspects of information-theoretic topics (62B10)

Related Items (2)

Joint modeling of longitudinal drug using pattern and time to first relapse in cocaine dependence treatment data ⋮ Optimization of the number of components in the mixed model using multi-criteria decision-making

Uses Software

• LBFGS-B
• SemiPar

Cites Work

• Unnamed Item
• Unnamed Item
• Unnamed Item
• Estimating the dimension of a model
• Nonparametric Mixed Effects Models for Unequally Sampled Noisy Curves
• Joint modelling of paired sparse functional data using principal components
• Semiparametric Regression
• Principal component models for sparse functional data
• A Limited Memory Algorithm for Bound Constrained Optimization
• The Estimation of Prediction Error
• Functional Data Analysis for Sparse Longitudinal Data

This page was built for publication: Model selection using modified AIC and BIC in joint modeling of paired functional data