Functionalities for modelling functional data with multidimensional inputs, multivariate functional data, and non-separable and/or non-stationary covariance structure of function-valued processes. In addition, there are functionalities for functional regression models where the mean function depends on scalar and/or functional covariates and the covariance structure depends on functional covariates. The development version of the package can be found on <https://github.com/gpfda/GPFDA-dev>.
Version: | 3.1.1 |
Depends: | R (≥ 3.6) |
Imports: | Rcpp (≥ 1.0.2), splines, mgcv, fields, interp, stats, graphics, grDevices, fda, fda.usc |
LinkingTo: | Rcpp, RcppArmadillo |
Suggests: | MASS, mvtnorm, knitr, rmarkdown |
Published: | 2021-01-29 |
Author: | Jian Qing Shi, Yafeng Cheng, Evandro Konzen |
Maintainer: | Evandro Konzen <gpfda.r at gmail.com> |
License: | GPL-3 |
NeedsCompilation: | yes |
In views: | FunctionalData |
CRAN checks: | GPFDA results |
Reference manual: | GPFDA.pdf |
Vignettes: |
co2 gpfr gpr_ex1 gpr_ex2 mgpr nsgpr |
Package source: | GPFDA_3.1.1.tar.gz |
Windows binaries: | r-devel: GPFDA_3.1.1.zip, r-release: GPFDA_3.1.1.zip, r-oldrel: GPFDA_3.1.1.zip |
macOS binaries: | r-release: GPFDA_3.1.1.tgz, r-oldrel: GPFDA_3.1.1.tgz |
Old sources: | GPFDA archive |
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