fdarep {fdarep}

fdarep: Two-Dimensional FPCA, Marginal FPCA, and Product FPCA for Repeated Functional Data

Description

fdarep for Functional Data Analysis

Details

fdarep is a versatile package that provides implementation of various methods of Functional Data Analysis (FDA) for repeated functional data.

References: Chen, K., Delicado, P., & Müller, H. G. (2017). Modelling function-valued stochastic processes, with applications to fertility dynamics. Journal of the Royal Statistical Society Series B: Statistical Methodology, 79(1), 177-196. Chen, K., & Müller, H. G. (2012). Modeling repeated functional observations. Journal of the American Statistical Association, 107(500), 1599-1609. Hall, P., Müller, H. G., & Wang, J. L. (2006). Properties of principal component methods for functional and longitudinal data analysis. Yao, F., Müller, H. G., & Wang, J. L. (2005). Functional data analysis for sparse longitudinal data. Journal of the American statistical association, 100(470), 577-590.

fdarep is a comprehensive package that directly implements fitting of the following models for repeated functional data: – Two-dimensional FPCA for dense repeated functional data – Marginal FPCA for dense repeated functional data – Product FPCA for dense repeated functional data – Marginal FPCA for sparse repeated functional data – Product FPCA for sparse repeated functional data

Maintainer: Poorbita Kundu [e-mail]

Author(s)

Poorbita Kundu [e-mail] Changbo Zhu Kehui Chen Pedro Delicado Su I Iao Hang Zhou Han Chen Muqing Cui

Hans-Georg Müller [e-mail] Jane-Ling Wang [e-mail]

See Also

Useful links:

• https://github.com/functionaldata/tFDArep

• Report bugs at https://github.com/functionaldata/tFDArep/issues