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Routines for re-scaling isotope maps using known-origin tissue isotope data, assigning origin of unknown samples, and summarizing and assessing assignment results. Methods are adapted from Wunder (2010, in ISBN:9789048133536) and Vander Zanden, H. B. et al. (2014) <doi:10.1111/2041-210X.12229> as described in Ma, C. et al. (2020) <doi:10.1111/2041-210X.13426>.
Version: | 2.4.1 |
Depends: | R (≥ 3.5) |
Imports: | mvnfast, rlang, geosphere, terra (≥ 1.7-23) |
Suggests: | knitr, rmarkdown, testthat, covr |
Published: | 2024-05-30 |
DOI: | 10.32614/CRAN.package.assignR |
Author: | Chao Ma, Gabe Bowen |
Maintainer: | Gabe Bowen <gabe.bowen at utah.edu> |
License: | GPL-3 |
NeedsCompilation: | no |
Language: | en-US |
Citation: | assignR citation info |
Materials: | README NEWS |
CRAN checks: | assignR results |
Reference manual: | assignR.pdf |
Vignettes: |
assignR Examples |
Package source: | assignR_2.4.1.tar.gz |
Windows binaries: | r-devel: assignR_2.4.1.zip, r-release: assignR_2.4.1.zip, r-oldrel: assignR_2.4.1.zip |
macOS binaries: | r-release (arm64): assignR_2.4.1.tgz, r-oldrel (arm64): assignR_2.4.1.tgz, r-release (x86_64): assignR_2.4.1.tgz, r-oldrel (x86_64): assignR_2.4.1.tgz |
Old sources: | assignR archive |
Please use the canonical form https://CRAN.R-project.org/package=assignR to link to this page.
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.