crestr: A Probabilistic Approach to Reconstruct Past Climates Using Palaeoecological Datasets

Applies the CREST climate reconstruction method. It can be used using the calibration data that can be obtained through the package or by importing private data. An ensemble of graphical outputs were designed to facilitate the use of the package and the interpretation of the results. More information can be obtained from Chevalier (2022) <doi:10.5194/cp-18-821-2022>.

Version: 1.1.0
Depends: R (≥ 2.10)
Imports: clipr, DBI, methods, plyr, raster, rgdal, rgeos, RPostgres, scales, sp, stringr, viridis
Suggests: knitr, openxlsx, plot3D, rmarkdown, pals, RSQLite
Published: 2022-07-01
Author: Manuel Chevalier ORCID iD [aut, cre]
Maintainer: Manuel Chevalier <chevalier.manuel at gmail.com>
BugReports: https://github.com/mchevalier2/crestr/issues
License: MIT + file LICENSE
URL: https://github.com/mchevalier2/crestr, https://mchevalier2.github.io/crestr/index.html
NeedsCompilation: no
Language: en-us
Citation: crestr citation info
Materials: README NEWS
CRAN checks: crestr results

Documentation:

Reference manual: crestr.pdf
Vignettes: Calibration data for CREST
Get started
Formatting the data for crestr
A bit of Theory

Downloads:

Package source: crestr_1.1.0.tar.gz
Windows binaries: r-devel: crestr_1.1.0.zip, r-release: crestr_1.1.0.zip, r-oldrel: crestr_1.1.0.zip
macOS binaries: r-release (arm64): crestr_1.1.0.tgz, r-oldrel (arm64): crestr_1.1.0.tgz, r-release (x86_64): crestr_1.1.0.tgz, r-oldrel (x86_64): crestr_1.1.0.tgz
Old sources: crestr archive

Linking:

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