fdapace: Functional Data Analysis and Empirical Dynamics

A versatile package that provides implementation of various methods of Functional Data Analysis (FDA) and Empirical Dynamics. The core of this package is Functional Principal Component Analysis (FPCA), a key technique for functional data analysis, for sparsely or densely sampled random trajectories and time courses, via the Principal Analysis by Conditional Estimation (PACE) algorithm. This core algorithm yields covariance and mean functions, eigenfunctions and principal component (scores), for both functional data and derivatives, for both dense (functional) and sparse (longitudinal) sampling designs. For sparse designs, it provides fitted continuous trajectories with confidence bands, even for subjects with very few longitudinal observations. PACE is a viable and flexible alternative to random effects modeling of longitudinal data. There is also a Matlab version (PACE) that contains some methods not available on fdapace and vice versa. Updates to fdapace were supported by grants from NIH Echo and NSF DMS-1712864 and DMS-2014626. Please cite our package if you use it (You may run the command citation("fdapace") to get the citation format and bibtex entry). References: Wang, J.L., Chiou, J., Müller, H.G. (2016) <doi:10.1146/annurev-statistics-041715-033624>; Chen, K., Zhang, X., Petersen, A., Müller, H.G. (2017) <doi:10.1007/s12561-015-9137-5>.

Version:	0.6.0
Imports:	Rcpp (≥ 0.11.5), Hmisc, MASS, Matrix, pracma, numDeriv
LinkingTo:	Rcpp, RcppEigen
Suggests:	plot3D, rgl, aplpack, mgcv, ks, gtools, knitr, rmarkdown, EMCluster, minqa, testthat
Published:	2024-07-03
DOI:	10.32614/CRAN.package.fdapace
Author:	Yidong Zhou [cre, aut], Han Chen [aut], Su I Iao [aut], Poorbita Kundu [aut], Hang Zhou [aut], Satarupa Bhattacharjee [aut], Cody Carroll [aut], Yaqing Chen [aut], Xiongtao Dai [aut], Jianing Fan [aut], Alvaro Gajardo [aut], Pantelis Z. Hadjipantelis [aut], Kyunghee Han [aut], Hao Ji [aut], Changbo Zhu [aut], Paromita Dubey [ctb], Shu-Chin Lin [ctb], Hans-Georg Müller [cph, ths, aut], Jane-Ling Wang [cph, ths, aut]
Maintainer:	Yidong Zhou <ydzhou at ucdavis.edu>
BugReports:	https://github.com/functionaldata/tPACE/issues
License:	BSD_3_clause + file LICENSE
URL:	https://github.com/functionaldata/tPACE
NeedsCompilation:	yes
Language:	en-US
Citation:	fdapace citation info
Materials:	README NEWS
In views:	FunctionalData
CRAN checks:	fdapace results

Documentation:

Reference manual:	fdapace.pdf
Vignettes:	Completion of Functional Fragments Introduction to fdapace

Downloads:

Package source:	fdapace_0.6.0.tar.gz
Windows binaries:	r-devel: fdapace_0.6.0.zip, r-release: fdapace_0.6.0.zip, r-oldrel: fdapace_0.6.0.zip
macOS binaries:	r-release (arm64): fdapace_0.6.0.tgz, r-oldrel (arm64): fdapace_0.6.0.tgz, r-release (x86_64): fdapace_0.6.0.tgz, r-oldrel (x86_64): fdapace_0.6.0.tgz
Old sources:	fdapace archive

Reverse dependencies:

Reverse imports:

fdaconcur, fdadensity, fdapaceShiny, fdaPOIFD, fdarep, fgm, frechet, ftsa, KFPCA, longke, longsurr, MJMbamlss, mrct, SLFPCA, WRI

Linking:

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