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Collection of several algorithms to obtain archetypoids with small and large databases, and with both classical multivariate data and functional data (univariate and multivariate). Some of these algorithms also allow to detect anomalies (outliers). Please see Vinue and Epifanio (2020) <doi:10.1007/s11634-020-00412-9>.
Version: | 1.2.1 |
Depends: | R (≥ 3.4.0) |
Imports: | Anthropometry, archetypes, FNN, foreach, graphics, nnls, parallel, stats, tolerance, univOutl, utils |
Suggests: | doParallel, fda |
Published: | 2020-08-04 |
DOI: | 10.32614/CRAN.package.adamethods |
Author: | Guillermo Vinue, Irene Epifanio |
Maintainer: | Guillermo Vinue <Guillermo.Vinue at uv.es> |
License: | GPL-2 | GPL-3 [expanded from: GPL (≥ 2)] |
URL: | https://www.r-project.org |
NeedsCompilation: | no |
Materials: | NEWS |
CRAN checks: | adamethods results |
Reference manual: | adamethods.pdf |
Package source: | adamethods_1.2.1.tar.gz |
Windows binaries: | r-devel: adamethods_1.2.1.zip, r-release: adamethods_1.2.1.zip, r-oldrel: adamethods_1.2.1.zip |
macOS binaries: | r-release (arm64): adamethods_1.2.1.tgz, r-oldrel (arm64): adamethods_1.2.1.tgz, r-release (x86_64): adamethods_1.2.1.tgz, r-oldrel (x86_64): adamethods_1.2.1.tgz |
Old sources: | adamethods 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.