resemble: Memory-Based Learning in Spectral Chemometrics

Functions for dissimilarity analysis and memory-based learning (MBL, a.k.a local modeling) in complex spectral data sets. Most of these functions are based the methods presented in Ramirez-Lopez et al. (2013) <doi:10.1016/j.geoderma.2012.12.014>.

Version: 2.0.0
Depends: R (≥ 3.5.0)
Imports: foreach, iterators, Rcpp (≥ 1.0.3), mathjaxr (≥ 1.0), magrittr (≥ 1.5.0), lifecycle (≥ 0.2.0), data.table (≥ 1.9.8)
LinkingTo: Rcpp, RcppArmadillo
Suggests: prospectr, parallel, doParallel, testthat, formatR, rmarkdown, bookdown, knitr
Published: 2020-11-09
Author: Leonardo Ramirez-Lopez [aut, cre], Antoine Stevens [aut, ctb], Raphael Viscarra Rossel [ctb], Craig Lobsey [ctb], Alex Wadoux [ctb], Timo Breure [ctb]
Maintainer: Leonardo Ramirez-Lopez <ramirez.lopez.leo at>
License: MIT + file LICENSE
NeedsCompilation: yes
Citation: resemble citation info
Materials: README NEWS
CRAN checks: resemble results


Reference manual: resemble.pdf
Vignettes: Modelling complex spectral data with the resemble package


Package source: resemble_2.0.0.tar.gz
Windows binaries: r-devel:, r-devel-UCRT:, r-release:, r-oldrel:
macOS binaries: r-release (arm64): resemble_2.0.0.tgz, r-release (x86_64): resemble_2.0.0.tgz, r-oldrel: resemble_2.0.0.tgz
Old sources: resemble archive


Please use the canonical form to link to this page.