Package: fdapace
Type: Package
Title: Functional Data Analysis and Empirical Dynamics
URL: https://github.com/functionaldata/tPACE
BugReports: https://github.com/functionaldata/tPACE/issues
Version: 0.5.2
Encoding: UTF-8
Date: 2020-02-13,
Authors@R: c(person("Yaqing","Chen", email="yaqchen@ucdavis.edu", role=c("aut","cre")),
    person("Cody","Carroll", email="cjcarroll@ucdavis.edu", role=c("aut")),
    person("Xiongtao","Dai", email="dai@ucdavis.edu", role=c("aut")),
    person("Jianing","Fan", role=c("aut")),
    person("Pantelis Z.","Hadjipantelis", role=c("aut")),
    person("Kyunghee","Han", role="aut"),
    person("Hao","Ji", role=c("aut")),
    person("Shu-Chin", "Lin", role="ctb"),
    person("Paromita", "Dubey", role="ctb"),
    person("Alvaro", "Gajardo", role="ctb"),
    person("Hans-Georg", "Mueller", role=c("cph","ths","aut")),
    person("Jane-Ling", "Wang", role=c("cph","ths","aut"))) 
Maintainer: Yaqing Chen <yaqchen@ucdavis.edu>
Description: 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. 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>.
License: BSD_3_clause + file LICENSE
LazyData: false
Imports: Rcpp (>= 0.11.5), Hmisc, MASS, Matrix, pracma, numDeriv
LinkingTo: Rcpp, RcppEigen
Suggests: plot3D, rgl, aplpack, mgcv, ks, gtools, knitr, EMCluster,
        minqa, testthat
NeedsCompilation: yes
RoxygenNote: 6.1.1.9000
VignetteBuilder: knitr
Packaged: 2020-02-14 23:32:10 UTC; ychen
Author: Yaqing Chen [aut, cre],
  Cody Carroll [aut],
  Xiongtao Dai [aut],
  Jianing Fan [aut],
  Pantelis Z. Hadjipantelis [aut],
  Kyunghee Han [aut],
  Hao Ji [aut],
  Shu-Chin Lin [ctb],
  Paromita Dubey [ctb],
  Alvaro Gajardo [ctb],
  Hans-Georg Mueller [cph, ths, aut],
  Jane-Ling Wang [cph, ths, aut]
Repository: CRAN
Date/Publication: 2020-02-15 21:20:11 UTC
