Nothing
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>.
Getting started
Browse package contents
Package details |
|
|---|---|
| Author | Leonardo Ramirez-Lopez [aut, cre] (ORCID: <https://orcid.org/0000-0002-5369-5120>), Antoine Stevens [aut, ctb] (ORCID: <https://orcid.org/0000-0002-1588-7519>), Claudio Orellano [ctb], Raphael Viscarra Rossel [ctb] (ORCID: <https://orcid.org/0000-0003-1540-4748>), Alex Wadoux [ctb] (ORCID: <https://orcid.org/0000-0001-7325-9716>) |
| Maintainer | Leonardo Ramirez-Lopez <ramirez.lopez.leo@gmail.com> |
| License | MIT + file LICENSE |
| Version | 2.2.4 |
| URL | http://l-ramirez-lopez.github.io/resemble/ |
| Package repository | View on CRAN |
| Installation |
Install the latest version of this package by entering the following in R:
|
Try the resemble package in your browser
Any scripts or data that you put into this service are public.
