Regression and similarity evaluation for memory-based learning
in spectral chemometrics.
Leonardo Ramirez-Lopez and Antoine Stevens
This package implements functions for spectral
similarity/dissimilarity analysis and memory-based learning (MBL) for
non-linear modelling in complex spectral datasets. MBL is
also known as local modelling in the chemometrics literature.

foreach, iterators, pls, Rcpp (>= 0.11.0)

Regression and Similarity Evaluation for Memory-Based Learning
in Spectral Chemometrics
Leonardo Ramirez-Lopez [aut, cre], Antoine Stevens [aut]
Implementation of functions for spectral similarity/dissimilarity
analysis and memory-based learning (MBL) for non-linear modeling
in complex spectral datasets. MBL is also known as local modeling
in the chemometrics literature.

Implementation of functions for spectral similarity/dissimilarity
analysis and memory-based learning (MBL) for non-linear modeling
in complex spectral datasets. In chemometrics MBL is also known as local modeling.

Memory-Based Learning in Spectral Chemometrics
Leonardo Ramirez-Lopez [aut, cre],
Antoine Stevens [aut, ctb],
Raphael Viscarra Rossel [ctb],
Craig Lobsey [ctb],
Alex Wadoux [ctb],
Timo Breure [ctb]
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>.
foreach, iterators, Rcpp (>= 1.0.3), mathjaxr (>= 1.0),
magrittr (>= 1.5.0), lifecycle (>= 0.2.0), data.table (>=
1.9.8)
prospectr, parallel, doParallel, testthat, formatR,
rmarkdown, bookdown, knitr

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]
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>.