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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 |
Reference manual: | fdapace.pdf |
Vignettes: |
Completion of Functional Fragments Introduction to fdapace |
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 imports: | fdaconcur, fdadensity, fdapaceShiny, fdaPOIFD, fdarep, fgm, frechet, ftsa, KFPCA, longke, longsurr, MJMbamlss, mrct, SLFPCA, WRI |
Please use the canonical form https://CRAN.R-project.org/package=fdapace to link to this page.
These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.