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Provides tools to build quantitative chemometric models and applications for near-infrared (NIR) sensors. Chemometric regression models are based on partial least squares regression as described by Wold (1975) <doi:10.1016/B978-0-12-103950-9.50017-4> and modified partial least squares regression as described by Shenk and Westerhaus (1991) <doi:10.2135/cropsci1991.0011183X003100020049x>, with further discussion by Westerhaus (2014) <doi:10.1255/nirn.1492>.
| Version: | 0.6.4 |
| Depends: | R (≥ 4.2.0) |
| Imports: | callr, digest (≥ 0.6), foreach, mathjaxr (≥ 1.0), plotly (≥ 4.0), prospectr (≥ 0.2.10), quarto, uuid, withr, zip, readxl, jsonlite, Rcpp |
| LinkingTo: | Rcpp, RcppArmadillo |
| Suggests: | knitr, testthat, covr, doParallel, parallel, devtools |
| Published: | 2026-06-30 |
| DOI: | 10.32614/CRAN.package.proximetricsR (may not be active yet) |
| Author: | Leonardo Ramirez-Lopez
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| Maintainer: | Leonardo Ramirez-Lopez <ramirez-lopez.l at buchi.com> |
| BugReports: | https://github.com/l-ramirez-lopez/proximetricsr/issues |
| License: | MIT + file LICENSE |
| URL: | https://github.com/l-ramirez-lopez/proximetricsr |
| NeedsCompilation: | yes |
| Citation: | proximetricsR citation info |
| Materials: | README, NEWS |
| CRAN checks: | proximetricsR results |
| Package source: | proximetricsR_0.6.4.tar.gz |
| Windows binaries: | r-devel: proximetricsR_0.6.4.zip, r-release: not available, r-oldrel: proximetricsR_0.6.4.zip |
| macOS binaries: | r-release (arm64): proximetricsR_0.6.4.tgz, r-oldrel (arm64): proximetricsR_0.6.4.tgz, r-release (x86_64): proximetricsR_0.6.4.tgz, r-oldrel (x86_64): proximetricsR_0.6.4.tgz |
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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.
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