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Some methods for the inference and clustering of univariate and multivariate functional data, using a generalization of Mahalanobis distance, along with some functions useful for the analysis of functional data. For further details, see Martino A., Ghiglietti, A., Ieva, F. and Paganoni A. M. (2017) <doi:10.48550/arXiv.1708.00386>.
Version: | 1.0.1 |
Depends: | R (≥ 3.3.0) |
Imports: | graphics, stats |
Suggests: | knitr, rmarkdown |
Published: | 2018-04-06 |
DOI: | 10.32614/CRAN.package.gmfd |
Author: | Andrea Martino [aut, cre], Andrea Ghiglietti [aut], Francesca Ieva [aut], Anna Maria Paganoni [aut] |
Maintainer: | Andrea Martino <andrea.martino at polimi.it> |
License: | GPL-3 |
NeedsCompilation: | no |
CRAN checks: | gmfd results |
Reference manual: | gmfd.pdf |
Vignettes: |
gmfd |
Package source: | gmfd_1.0.1.tar.gz |
Windows binaries: | r-devel: gmfd_1.0.1.zip, r-release: gmfd_1.0.1.zip, r-oldrel: gmfd_1.0.1.zip |
macOS binaries: | r-release (arm64): gmfd_1.0.1.tgz, r-oldrel (arm64): gmfd_1.0.1.tgz, r-release (x86_64): gmfd_1.0.1.tgz, r-oldrel (x86_64): gmfd_1.0.1.tgz |
Old sources: | gmfd archive |
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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.