Package: growfunctions
Type: Package
Title: Bayesian Non-Parametric Dependent Models for Time-Indexed
        Functional Data
Version: 0.14
Date: 2018-03-30
Author: Terrance Savitsky
Maintainer: Terrance Savitsky <tds151@gmail.com>
Description: Estimates a collection of time-indexed functions under
    either of Gaussian process (GP) or intrinsic Gaussian Markov
    random field (iGMRF) prior formulations where a Dirichlet process
    mixture allows sub-groupings of the functions to share the same
    covariance or precision parameters.  The GP and iGMRF formulations
    both support any number of additive covariance or precision terms,
    respectively, expressing either or both of multiple trend and
    seasonality.
License: GPL (>= 3)
Depends: R (>= 3.2.2), Rcpp (>= 0.11.6)
LinkingTo: Rcpp (>= 0.12.16), RcppArmadillo (>= 0.8.400.0.0)
Imports: spam(>= 0.41-0), mvtnorm(>= 1.0-0), ggplot2(>= 1.0.1),
        reshape2(>= 1.2.2)
Suggests: testthat(>= 0.8.1)
Collate: 'MSPE.R' 'cps.R' 'gen_informative_sample.R' 'gpdpgrow.R'
        'gmrfdpgrow.R' 'gp_car_fit_compare_facet.R' 'gp_cluster_plot.R'
        'gp_informative_compare_plot.R' 'help.R' 'plot_cluster.R'
        'predict_plot.R'
RoxygenNote: 6.0.1
NeedsCompilation: yes
Packaged: 2018-03-31 03:05:18 UTC; savitsky_t
Repository: CRAN
Date/Publication: 2018-03-31 03:33:01 UTC
Built: R 4.1.0; x86_64-w64-mingw32; 2020-08-03 12:55:03 UTC; windows
Archs: i386, x64
