fdapace: Functional Data Analysis and Empirical Dynamics

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 or numerical integration. PACE is useful for the analysis of data that have been generated by a sample of underlying (but usually not fully observed) random trajectories. It does not rely on pre-smoothing of trajectories, which is problematic if functional data are sparsely sampled. PACE provides options for functional regression and correlation, for Longitudinal Data Analysis, the analysis of stochastic processes from samples of realized trajectories, and for the analysis of underlying dynamics. The core computational algorithms are implemented using the 'Eigen' C++ library for numerical linear algebra and 'RcppEigen' "glue".

Version: 0.4.1
Imports: Rcpp (≥ 0.11.5), Hmisc, MASS, Matrix, pracma, numDeriv
LinkingTo: Rcpp, RcppEigen
Suggests: plot3D, rgl, aplpack, mgcv, ks, gtools, knitr, EMCluster, minqa, testthat
Published: 2019-03-19
Author: Xiongtao Dai [aut], Pantelis Z. Hadjipantelis [aut, cre], Kynghee Han [aut], Hao Ji [aut], Shu-Chin Lin [ctb], Hans-Georg Mueller [cph, ths], Jane-Ling Wang [cph, ths]
Maintainer: Pantelis Z. Hadjipantelis <pantelis at ucdavis.edu>
BugReports: https://github.com/functionaldata/tPACE/issues
License: BSD_3_clause + file LICENSE
URL: https://github.com/functionaldata/tPACE
NeedsCompilation: yes
Materials: NEWS
In views: FunctionalData
CRAN checks: fdapace results


Reference manual: fdapace.pdf
Vignettes: Introduction to fdapace
Package source: fdapace_0.4.1.tar.gz
Windows binaries: r-devel: fdapace_0.4.1.zip, r-release: fdapace_0.4.1.zip, r-oldrel: fdapace_0.4.1.zip
OS X binaries: r-release: fdapace_0.4.1.tgz, r-oldrel: fdapace_0.4.1.tgz
Old sources: fdapace archive

Reverse dependencies:

Reverse depends: LCox
Reverse imports: fdadensity


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