Package: resemble 2.2.2

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 on the methods presented in Ramirez-Lopez et al. (2013) <doi:10.1016/j.geoderma.2012.12.014>.

Authors:Leonardo Ramirez-Lopez [aut, cre], Antoine Stevens [aut, ctb], Claudio Orellano [ctb], Raphael Viscarra Rossel [ctb], Zefang Shen [ctb], Craig Lobsey [ctb], Alex Wadoux [ctb]

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resemble.pdf |resemble.html✨
resemble/json (API)
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Bug tracker:https://github.com/l-ramirez-lopez/resemble/issues

On CRAN:

chemoinformaticschemometricsinfrared-spectroscopylazy-learninglocal-regressionmachine-learningmemory-based-learningnirpedometricssoil-spectroscopyspectral-dataspectral-libraryspectroscopy

16 exports 20 stars 2.20 score 12 dependencies 27 scripts 421 downloads

Last updated 1 years agofrom:929f60aab0. Checks:OK: 4 NOTE: 5. Indexed: yes.

Exports:cor_dissdissimilarityf_dissget_predictionslocal_fit_gprlocal_fit_plslocal_fit_waplsmblmbl_controlortho_dissortho_projectionpc_projectionpls_projectionsearch_neighborssidsim_eval

Dependencies:clicodetoolsdata.tableforeachglueiteratorslifecyclemagrittrmathjaxrRcppRcppArmadillorlang