Evaluation of prediction performance of smaller regions of spectra for Chemometrics. Segmentation of spectra, evolving dimensions regions and sliding windows as selection methods. Election of the best model among those computed based on error metrics. Chen et al.(2017) <doi:10.1007/s00216-017-0218-9>.
Version: | 0.1.0 |
Depends: | R (≥ 2.10) |
Imports: | dplyr, ggplot2, grDevices, mdatools, readr, stringr, tidyr, tidyverse |
Suggests: | testthat (≥ 3.0.0) |
Published: | 2023-08-09 |
DOI: | 10.32614/CRAN.package.windows.pls |
Author: | Elia Gonzato [aut, cre, cph] |
Maintainer: | Elia Gonzato <elia.gonzato at outlook.it> |
BugReports: | https://github.com/egonzato/windows.pls/issues |
License: | MIT + file LICENSE |
URL: | https://github.com/egonzato/windows.pls |
NeedsCompilation: | no |
Materials: | README |
CRAN checks: | windows.pls results |
Reference manual: | windows.pls.pdf |
Package source: | windows.pls_0.1.0.tar.gz |
Windows binaries: | r-devel: windows.pls_0.1.0.zip, r-release: windows.pls_0.1.0.zip, r-oldrel: windows.pls_0.1.0.zip |
macOS binaries: | r-release (arm64): windows.pls_0.1.0.tgz, r-oldrel (arm64): windows.pls_0.1.0.tgz, r-release (x86_64): windows.pls_0.1.0.tgz, r-oldrel (x86_64): windows.pls_0.1.0.tgz |
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